FIJI: Energy and Transport Data Audit and Data Management Assessment for Electrification of the Transport Sector

Final Report September 2019

Contents

Illustrations ...... 3 Abbreviations ...... 4 EXECUTIVE SUMMARY ...... 5 1. BACKGROUND TO THE PROJECT ...... 7 Project Phases ...... 8 Research Undertaken ...... 9 2. BENEFITS AND COSTS OF ELECTRIFIED TRANSPORT ...... 10 Potential Positive Impacts ...... 10 Lower greenhouse gas emissions ...... 10 Reduced air pollution ...... 13 More pedestrian-friendly mixed traffic zones ...... 13 Source of “second life” batteries for PV systems ...... 14 Consistency with “sustainability” objectives and branding ...... 14 Changes in vehicle import and operating costs ...... 15 Impact on national balance of payments ...... 17 Potential Negatives ...... 18 Higher greenhouse gas emissions ...... 18 Vehicle costs ...... 18 Cost of charging infrastructure ...... 19 Battery costs (including end-of-life disposal) ...... 19 3. CATEGORIES OF INFORMATION REQUIRED ...... 21 Vehicles ...... 21 Number and types of Vehicles...... 21 Market Conditions ...... 27 Technology and Efficiency ...... 28 Maritime ...... 29 Travel ...... 30 Vehicle Usage ...... 30 Fuels ...... 31 4. ORGANISING AND FACILITATING INFORMATION FLOWS ...... 33 Agency Roles ...... 33 Constraints, bottlenecks and gaps ...... 35 Constraints ...... 35 Bottlenecks ...... 36 Gaps ...... 37 International Data ...... 37 5. DATA FRAMEWORK AND STRATEGY (DFS) ...... 39 A. Organisational arrangements ...... 39 B. Policy studies and modelling ...... 41 C. Analyses of existing and expected data ...... 44 D. Planning and delivering new data acquisitions ...... 46 Conclusions ...... 47 REFERENCES ...... 49

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 2 Documents ...... 49 Websites ...... 49 APPENDIX 1. STAKEHOLDERS CONSULTED ...... 50 APPENDIX 2. FIRST STAKEHOLDER WORKSHOP, 28 JUNE 2019 ...... 52 APPENDIX 3. SECOND STAKEHOLDER WORKSHOP, 6 AUGUST 2019 ...... 54 APPENDIX 4. VEHICLE ADDITIONS AND RETIREMENTS ...... 56

Illustrations

Figure 1 Transition from current situation to LEDS ...... 7 Figure 2 Main Data Categories and Collection Agencies ...... 22 Figure 3 Total vehicle registrations, 2001 - 2018 ...... 26 Figure 4 New registrations each year, 2001 – 2018 ...... 26 Figure 5 The “Information Pyramid” ...... 34 Figure 6 Annual retirements from the motor vehicle register ...... 56 Figure 7 Trend in total registrations ...... 56 Figure 8 Trend in annual retirements ...... 57

Table 1 Emissions-intensities of an ICV, HV and EV of comparable size ...... 12 Table 2 Emissions intensities of vehicles under different generation fuel mixes ...... 12 Table 3 Example of annual revenue contribution calculations...... 16 Table 4 Example of 10-year revenue calculation (new vehicle, CIF value $30,000) .... 17 Table 5 Example of 10-year revenue calculation (used vehicle, CIF value $12,000) .... 17 Table 6 Summary of major data collections reviewed to date ...... 23 Table 7 Extract from LTA registration database (2015) ...... 24 Table 8 Extract from FRCS Motor Vehicle Landing Costs (Jul-Sept 2018) ...... 24 Table 9 Total Vehicle Registrations by New/Used, 2015 ...... 27 Table 10 Summary and indicative timeline of tasks and projects ...... 48

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 3 Abbreviations

BAU Business as Usual CEO Chief Executive Officer DFS Data Framework and Strategy DOE Department of Energy EFL Energy Fiji Limited EV Electric vehicle FBOS Fiji Bureau of Statistics FRCS Fiji Revenue and Customs Service GGGI Global Green Growth Institute LEDS Low-emissions development strategy HIES Household Income and Expenditure Survey HTS Household Travel Survey HV Hybrid vehicle ICV Internal Combustion Vehicle LHD Left Hand Drive (i.e. steering wheel on the left of the vehicle) LTA Land Transport Authority MOIT Ministry of Infrastructure and transport MOU Memorandum of Understanding MSAF Maritime Safety Authority of Fiji NMT Non-motorized transport NTPD National Transport Planning Database PHV Plug hybrid vehicle PT Public transport PV Photovoltaic RHD Right Hand Drive (as in Fiji) TPU Transport Planning Unit TOU Time of use UNESCAP United Nations Economic and Social Commission for Asia and the Pacific VAT Value added tax VKT Vehicle-kilometres travelled

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 4 Executive Summary

This is the final report on an Energy and Transport Data Audit and Data Collection Strategy to support planning for the electrification of the transport sector in Fiji (The Strategy is also called the Data Framework and Strategy, or DFS). The project was undertaken with the kind co-operation and assistance of the Ministry of Infrastructure and Transport (MOIT), and in particular the Transport Planning Unit (TPU) and the Department of Energy (DOE) of MOIT.

Adoption of electric vehicles (EVs) for land transport was one of the main strategies for reducing emissions identified in the Low Energy Development Strategy 2018-2050. Electrification may also have a more limited role in reducing maritime emissions. The aim of the project is to help provide a policy and planning bridge between the present situation and the first stage of the LEDS strategy.

The project proceeded in four stages: commencement, research and preparation of a data audit (followed by a first stakeholder workshop), development of a draft strategy and action plan (followed by a second stakeholder workshop), and completion (this report, together with other materials).

All public policies have both benefits and costs. Policy makers are not able to assess these realistically unless they have the necessary information, and they cannot be sure they have the necessary information without a preliminary assessment of the likely positive and negative outcomes of the policy. Then they will be in a position to collect the information required, calculate the cost and benefits and make an informed decision.

Chapter 2 describes the main impacts of likely positive outcomes (benefits) and negative outcomes (costs) from the introduction of electric vehicles and vessels to Fiji. In many cases potential positive impacts could turn out negative, and vice versa. It gives several worked examples of impact calculations that could be carried out once the necessary information becomes available.

Chapter 3 summaries the specific categories of data required to undertake the policy studies and evaluations, and the agencies responsible for acquiring and managing it. The data categories are been grouped into three inter-related clusters:

• Fuels (transport and generation) • Vehicles (transport equipment); and • Travel and mobility.

For fuels and transport equipment, information is required for all stages from import (and before import in some cases) to distribution, use and disposal. The travel behaviour relevant to this project takes place within Fiji. The chapter analyses the content, structure and accessibility of the main collections, and suggests how thee could be made more useful with greater co-ordination.

Chapter 4 identifies legal constraints and administrative bottlenecks in the flow of information between agencies and presents the data framework in terms of an

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 5 “information pyramid.” The development of transport electrification policy (the apex of the pyramid) needs to be solidly based on actual data.

As it happens, the base of the pyramid is well established already, although some gaps are identified in the chapter. Several agencies routinely collect relevant data, although they do not necessarily make it all public, or not in a consistent and accessible form. The chapter also reviews the use of data from international sources.

Chapter 5 presents the recommended Data Framework and Strategy (DFS). The objective of the DFS is to enable MOIT to prepare well-founded advice on the costs and benefits of transport electrification from a national perspective.

The DFS is divided into Tasks and Projects. Tasks are on-going activities, including managing information flows, data collections and access, planning data acquisitions, combining existing data sets, analysing new data sets as they become available and reporting progress and problems. Projects are distinct studies needed to support the higher levels in the information pyramid. Some may only need to be done once, and others repeated occasionally as data improves.

Chapter 5 identifies 24 distinct activities (on-going tasks and projects) and presents an indicative 3-year timeline (further detail is given in a separate report to MOIT). It is recognised that the work will depend on the time and financial resources available, and projects are staggered to spread the load. There are 7 high priority activities, involved with establishing the DFS and informing two of the threshold issues that policy-makers will need to address:

• What will be the impact of transport electrification on national emissions?; and

• What will be the impact on government revenues and the national economy?

There are 6 activities rated medium-high priority and 11 rated as medium. All are considered necessary to build a sound basis for developing transport electrification, and in many cases will also support the general planning work of MOIT, and the TPU in particular.

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Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 6 1. Background to the Project

This is the final report on an Energy and Transport Data Audit and Data Collection Strategy to support planning for the electrification of the transport sector in Fiji.

Adoption of electric vehicles (EVs) for land transport was one of the main strategies for reducing emissions identified in the Low Energy Development Strategy 2018-2050 (LEDS), along with

• Adoption of hybrid vehicles (HVs)1; • Promotion of public transport (PT); • Promotion of non-motorized transport (NMT), including cycling; • Promotion of vehicle renewal and scrapping; • Promotion of biofuels; • Adoption of efficient new vehicles; and • Efficiency improvements in operating vehicles.

Electrification may also have a more limited role in reducing maritime emissions, especially as a possible alternative in the transition away from 2-stroke outboard engines. The Fiji LEDS estimates that in 2014 maritime emissions were 174 kt CO2, compared with 636 kt CO2 for land transport.

The aim of the project is to help provide a policy and planning bridge between the present situation and the first stage of the LEDS strategy (Figure 1)

Figure 1 Transition from current situation to LEDS

1 The actual recommendation in the LEDS (p79) was “Adoption of HEVs and EVs.” Hybrid vehicles (HVs) are sometimes called hybrid electric vehicles (HEVs) but as they have internal combustion engines and are fuelled solely by petroleum products they as better described as HVs. The fact that batteries and electric motors are involved in the drivetrain is not directly relevant to their tailpipe emissions, except that the energy recovered from braking makes them more fuel-efficient than conventional internal combustion vehicles (ICVs). HVs which can accept charge from an external power supply as well as on-board generation are called plug hybrid vehicles (PHVs). EVs have no internal combustion engine, and can only be charged from an external power supply.

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 7 Further policy development and implementation will rely on comprehensive and reliable information on a wide range of topics relevant to transport sector electrification. Some of this information already exists, but is not fully co-ordinated, as set out in Chapter 3 of this report. In other cases, initial data collections have been done, but need to be repeated at regular intervals to build up a reliable time series.

The first part of the project focussed on identifying, assessing, and applying existing information for policymaking, within the framework of the Sustainable Development Goal (SDG) on clean energy. It examined existing data collection, management, utilisation and sharing systems particularly in the context of electrification opportunities in land and maritime transport.

The second part of the project covered the next steps needed to create an enabling environment in terms of data for planning the transition to electric vehicles, immediate next studies needed, future energy data needs and how to obtain such data, initial mapping of roles of different agencies now and in future.

This report covers the entire project and includes recommendations.

Project Phases

The project proceeded in the following phases:

1. Commencement: clarify objectives, initial contact with main stakeholders, develop workplan, prepare inception report.2 2. Research and analysis: interview stakeholders, identify and acquire existing data collections, investigate patterns of data use. Summarise in a briefing paper, present results and obtain feedback from first workshop of stakeholders. 3. Strategy and action plan: Prepare energy data audit report, strategy action plan and recommendations in draft final report. Present to and obtain feedback from second workshop of stakeholders. 4. Completion: Final report (this document).

A draft report covering phase 2 was presented to a workshop of invited stakeholders in Suva on 28 June 2019.3 The findings of the draft report were validated during the workshop, the details of which are at Appendix 2.

A draft Data Management Strategy and Action Plan was presented to stakeholders for comment and feedback, at a second stakeholder workshop to in Suva on 6 August 2019. Details of the workshop are at Appendix 3. This report embodies the outcomes of both workshops.

This project is running in parallel with a detailed study of the electricity infrastructure requirements needed to support transport electrification on the island of Viti Levu.

2 FIJI: Energy and Transport Data Audit for Electrification of Transport; Inception Report to GGGI AND ESCAP April 2019 3 FIJI: Energy and Transport Data Audit for Electrification of Transport; Briefing Paper Prepared for the Ministry of Infrastructure and Transport of Fiji under a technical assistance project supported by the Global Green Growth Institute and funded by UNESCAP, June 2019

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 8 Research Undertaken

The information in this report was compiled from a number of sources:

• The LEDS and documents compiled for the LEDS; • Interviews with stakeholders carried out by the author and GGGI during a mission to Suva in March 2019, and additional interviews in the days before and after each workshop; • Published and unpublished documents and data collections identified during research and discussions; and • Internet research.

The References list the most relevant documents and websites of interest (in addition to those in footnotes) and Appendix 1 lists the organisations and stakeholders interviewed.

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 9 2. Benefits and Costs of Electrified Transport

This section describes the main impacts and likely positive outcomes (benefits) and negative outcomes (costs) from the introduction of electric vehicles and vessels to Fiji. In many cases potential positive impacts could turn out negative, and vice versa.

Potential Positive Impacts

Lower greenhouse gas emissions

Conventional vehicles combust liquid fuels in their engines. The combustion products are mainly carbon dioxide (CO2), with traces of other gases with a global warming potential: methane (CH4) and nitrous oxide (N2O). Oxides of nitrogen (mainly NO2) and sulphur (SO2), non-methane volatile organic compounds (NMVOC) and solid particulates are also emitted during combustion.

The amount of combustion products emitted per vehicle-km travelled (VKT) depends on the quantity of fuel consumed, the type of fuel (petrol, diesel or biofuels), the grade of fuel (e.g. the sulphur content of diesel) and the design and condition of the engine. Many countries set fuel consumption standards for new vehicles, expressed as maximum litres consumed per 100km travelled (or in the case of the USA, minimum miles travelled per US gallon consumed). These impose a limit on the amount of CO2 emitted per km or mile travelled. For compliance purposes the values are determined in laboratory testing; on-road fuel consumption tends to be significantly higher.

Many countries also set limits on other (non-CO2) emissions for new vehicles, and these have become more stringent over time. The European Union standards (termed Euro 1, Euro 2 etc.) have been adopted in many other countries, although more slowly than in the EU itself.4 One of the reasons why countries such as Fiji lag behind is fuel quality – the latest (Euro 6) standards for diesel powered vehicles can only be met by low-sulphur diesel fuel, which may not be available.5

Information required to make an informed judgement

The greenhouse gas emissions per VKT can be calculated by multiplying the emission factor of the fuel by the number of litres consumed per km. There are usually two emissions factors: one based on the chemical composition of the fuel itself (the Scope 1

4https://en.wikipedia.org/wiki/European_emission_standards 5 In August 2017 the Fiji Government noted that the average tested sulphur content of diesel fuel available in Fiji between 2014 and 2016 was 290 ppm, and approved a timetable for transition to setting maximum levels of 10 ppm (equivalent to Euro 5) by January 2018 – later changed to 1 January 2019. https://www.reinfofiji.com.fj/wp-content/uploads/2017/11/Memo-to-DoE.pdf. Interviewees were not able to confirm that this standard has been met, and several expressed the view that it has not.

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 10 factor) and the other (Scope 3) on the energy used to extract, refine and transport the fuel to the point where it is transferred to the vehicle. Scope 3 factors typically add about 5% to the Scope 1 factors but could be higher in island countries such as Fiji, where fuels have to be transported over longer distances.

6 For example, the Scope 1 emission factor for petrol is 2,313 g CO2-e per litre, and the Scope 3 factor is 123 g CO2-e per litre giving total emissions of 2,436 g CO2-e per litre. The Scope 1 emission factor for diesel is 2,722 g CO2-e per litre, and the Scope 3 factor 7 is 139 g CO2-e per litre, giving total emissions of 2,911 g CO2-e per litre.

Therefore a conventional petrol-powered internal combustion vehicle (ICV) with an on- road fuel consumption of 7.5 litres/100 km (0.075 litres per km) would emit 0.075 x 2,436 = 183 g CO2-e per km (Table 1).

Electric vehicles have no tailpipe emissions, but will create emissions from power generation, unless they are charged from a 100% renewable power supply. At present about half the energy generated by the Energy Fiji Limited (EFL) grid is from hydro and half from diesel.8

The Pacific Power Association reports that EFL has a thermal generation fuel use of 4.7 kWh/kg, or 3.9 kWh/litre (0.26 litres per kWh)9 giving emissions of 0.26 x 2,911 = 844 g CO2-e per kWh generated from fuel. However, only half the energy EFL sends out to its network is generated from fuel, and the rest is generated from renewable sources (mainly hydro) without emissions. Therefore, the average is 822/2 = 422 g CO2-e per kWh sent out.

The Pacific Power Association reports that EFL network losses are about 12% of the energy sent out. Therefore, the electricity supplied to EV chargers is (422/0.88) = 480 g CO2-e per kWh.

The electrical energy consumption of a Nissan Leaf EV, for example, is given as 16.5 kWh per 100 km, or 0.165 kWh/km when tested.10 It is assumed that the on-road energy use would be 50% higher, as is the case for ICVs and HVs (24.8 kWh/100 km). If all the energy were supplied from the EFL grid, using its current fuel mix, the emissions attributable to a Nissan Leaf would be 0.248 x 480 = 119 g CO2-e per km.

With the current generation mix, and EV would lead to about 35% less emissions than a conventional ICV of a similar size and annual mileage. However, substituting an EV for a HV would produce a much lower emissions benefit of only about 4% (Table 1).

If the generation mix were 100% renewable, then EVs would have a large emissions advantage (last column in Table 2). Until that point, however, the output of renewable generation on the system is constrained by the capacity (MW) of renewables installed

6 CO2-e (or CO2-equivalent) is a single value that sums the volume-weighted global warming potential of the mass of CO2, CH4 and N2O present in the combustion products. 7http://www.environment.gov.au/system/files/resources/80f603e7-175b-4f97-8a9b- 2d207f46594a/files/national-greenhouse-accounts-factors-july-2018.pdf 8 EFL Annual Report 2018. For the 5 years 2014-2018 the average thermal share of generation was 49%. 9 https://www.ppa.org.fj/wp-content/uploads/2019/09/2018-FY-Benchmarking-Report_update_220719- FINAL.pdf, p 10 https://ev-database.org/car/1106/Nissan-Leaf

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 11 and the natural variability of water, wind and sun. Whatever renewable generation is in place will be used to its maximum output, and any additional demand must be met by dispatchable fossil fuel sources, in this case diesel. Therefore, diesel will almost certainly remain the “marginal” generation fuel until the system is 100% renewable.

Table 1 Emissions-intensities of an ICV, HV and EV of comparable size Vehicle Tested energy On-road Annual GH-intensity Emissions per efficiency (a) energy energy use of energy km travelled efficiency (b) (c) consumed (g CO2-e/km) (+ 50% est.) Honda Jazz 1.5 5.0 7.5 litres/100km 1125 litres 2436 g CO2- 183 ICV litres/100km e/litre

Toyota Prius 3.4 5.1 litres/100km 765 litres 2436 g CO2- 124 1.8 HV litres/100km e/litre

Nissan Leaf EV 16.5 kWh/100 24.8 kWh/100 3,870 kWh 352 g CO2- 119 km km e/kWh (a) https://www.greenvehicleguide.gov.au/ (b) Assuming 50% margin over tested value; different standards, vehicle types and models may have different ratios in practice.11 (c) Assuming each vehicle travels

If the growth in energy use of EVs increases faster than the increase in output from renewable generation, then the quantum of diesel generation would have to increase, and each additional EV would lead to Fiji’s emissions being higher than would otherwise be the case. Projecting the emission trajectory in future years requires assumptions and modelling of the number of EVs, their contribution to the growth in total electricity demand and the generation mix of the EFL system. Also, the average fuel-efficiency of the conventional ICV and HV fleet may also improve over time, so reducing the apparent advantage of EVs.

Table 2 Emissions intensities of vehicles under different generation fuel mixes Vehicle Today’s generation Partial (constrained) 100% (unconstrained) mix renewable generation, renewable generation g CO2-e/km (a) diesel marginal generation Honda Jazz 1.5 ICV 183 183 183 Toyota Prius 1.8 HV 124 124 124 Nissan Leaf EV 119 ??? 0 (a) Table 1

Informed policy decisions about whether moving to EVs will reduce or increase Fiji’s greenhouse gas emissions will require projections of:

1. The average and total fuel consumption (litres/100 km) of the ICV fleet under “business as usual” (BAU) conditions in future years i.e. if there are no changes in current policy settings.

11 https://theicct.org/publications/laboratory-road-intl

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 12 2. The average energy efficiency (kWh/100 km) of the EVs that would be imported to Fiji under policy settings promoting EVs, and the total MWh that would be added to annual electricity demand on the grid.

3. The average and total fuel consumption (litres/100 km) of the non-electric ICV vehicle fleet under policy settings promoting EVs.

4. The total emissions from the electricity generation in each year under BAU and under the EV policy settings.

Reduced air pollution

The fact that EVs have no tailpipe emissions means that they will not contribute to local air pollution (SOx, NOx, NMVOCs and particulates). NMVOCs are also precursors of low-level ozone.

Replacing a poorly-maintained diesel vehicles with EVs carrying out the same task would be particularly beneficial.12 There may also be opportunities to introduce electrified modes when new bus, rail or ferry routes are planned.

Information required to make an informed judgement

It should be possible to project vehicle pollutant loads in Fiji’s main urban areas under both BAU and EV-supportive policy settings.

The TPU should be mindful of transport electrification benefits and opportunities early in the process of assessing new transport routes and corridors.

More pedestrian-friendly mixed traffic zones

EVs are particularly well suited to mixed traffic zones where pedestrians interact with vehicles. EVs are non-polluting and quiet (in fact, many EVs emit a warning noise at low speeds to alert pedestrians). Furthermore, electric propulsion is suited to a wide range of vehicle types and designs, so lighter purpose-built EVs could be used to transport passengers and local delivery freight within a designated zone.

The Central Suva area, which currently has high congestion and pollution from vehicle traffic, and vehicle-pedestrian conflicts, could be developed into an EV-intensive ICV- free zone. This could support a concentration of public charging stations, and so act as a nucleus or test-bed for the next phase of electrification.

Information required to make an informed judgement

The information required is not so much routine data collection or analysis but ensuring that traffic and urban planning agencies (e.g. Fiji Roads Authority, municipal councils) are aware of transport electrification benefits and opportunities early enough in the planning process. This will require better coordination between agencies.

12 https://ecsdev.org/ojs/index.php/ejsd/article/download/401/398

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 13

Source of “second life” batteries for PV systems

A small EV like a Nissan Leaf has about 200 kg of lithium-ion batteries.13 These are subjected to heavy usage and rapid charge-discharge cycles during use, and will eventually need to be replaced, possibly more than once, during the EV’s service life. The EV market is too recent for average service lives to determined and in any case the average EV service life in Fiji will depend on whether the vehicles are imported new or used.

Reconditioned EV batteries are still capable of lighter duties such as storage for PV systems, where charge and discharge rates are much lower, and less of the total battery capacity is drawn off in each cycle. “Second Life” facilities for reconditioning and repurposing EV batteries have recently been established in Japan.14

As Fiji has an extensive program of off—grid rural electrification, there could well be a local demand for reconditioned EV batteries for that purpose. It may be feasible to set up a battery reconditioning industry in Fiji once there is a steady supply of EV batteries. A facility of this kind would also help with the problem of dealing with the worn-out batteries of the present generation of hybrid vehicles.

Information required to make an informed judgement

A predictive model is required incorporating battery imports (in HVs and EVs and as separate units), service lives, reconditioning and disposal. The existing HV service industry in Fiji can give useful information in actual experience. Research will also be necessary on the battery loads and service lives of the types of EVs likely to be imported in future (whether as new or used vehicles). The model should yield the number of batteries available for reconditioning or scrapping in future years under both BAU and with-EVs scenarios. This information is essential to evaluating whether battery reconditioning or scrapping services would be viable, and the level of investment that would be needed to build this capability in Fiji.

Consistency with “sustainability” objectives and branding

EVs are certainly associated in the public mind with progress, environmental benefits and sustainability. As a country where international tourism is a major part of the economy, Fiji could derive marketing advantages from the visible presence of EVs.

Furthermore, about two thirds of international visitors are from Australia or New Zealand15, countries where there is a high level of interest in EVs. If the car rental fleets included EVs, and there were charging stations along the King’s Road and Queen’s Road, visitors could rent EVs as part of their holiday, and as a low-risk “test drive” with a view to buying an EV at home. The ports of call for cruise ships (Suva and Lautoka) could also offer business opportunities for visitors to rent EVs during post visits.

13 https://pushevs.com/2018/01/29/2018-nissan-leaf-battery-real-specs/ 14 https://www.japantimes.co.jp/news/2018/07/04/business/retired-electric-vehicle-batteries-find-second- life-chilling-beer-grilling-sausages/#.XQiGMEl7m70 15 Fiji Bureau of Statistics, Statistical News, 14 January 2019.

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 14

In the pacific region, at least one New Zealand rental company offers EVs.16 Australian rental car companies do not at present rent EVs, possibly due to the long drive distances and lack of public charging infrastructure between the main cities. 17 The rental car companies y started to rent hybrid cars about a decade ago (and still do), with a similar objective of offering an eco-friendly alternative and enabling prospective buyers to try new technologies at low risk.

The tourism sector also presents one of the best opportunities to introduce electrically- powered vessels. Many resorts operate small fleets of pleasure craft and fleet viewing craft. These may travel relatively short distances each day and tend to be berthed together overnight, favourable conditions for the operational constraints and charging requirements of electric outboards.

Information required to make an informed judgement

As this is a marketing benefit rather than a technical benefit and relies on knowing the attitudes and likely behaviour of a target group (visitors renting cars), special market surveys would be required. However, data on the number of rentals, the average driving distances and preferred routes by target groups would be necessary to plan an effective investigation.

In terms of electrically powered vessels, research is necessary on the numbers and operating patterns of tourism sector fleets in such specific segments.

Changes in vehicle import and operating costs

It is often stated that EVs are cheaper to operate than ICVs, but this depends on the relative taxation regimes for electricity and transport fuels, which are in the control of Government. While the Government may choose to permit early adopters of EVs to benefit from lower import duties and energy costs, if numbers build up as intended then the losses in revenue would greatly increase.

An EV contributes as much as an ICV or a HV of equal mass to the costs of traffic congestion and wear on the roads. It does not contribute directly to raising revenue from excise and value-added tax (VAT) on transport fuel but may contribute indirectly through the fuel consumed in generating the electricity it uses. If it is intended that transport electrification should be revenue-neutral it may be necessary to recover revenue from EVs in different ways, through special charges for road use or through the pricing of the electricity consumed for charging and/or the type of charging.

Table 3 shows an example of calculating the contribution of various vehicle types to annual government revenues, assuming current levels of import fiscal duty and VAT on fuels, and VAT on electricity. Under these assumptions an EV would contribute about $570 less to revenue annually than an ICV, and about $280 less than a HV.

16 https://www.europcar.co.nz/electric-vehicles 17 Despite the lack of commercial EV rentals in Australia there are peer-to-peer rentals available from private EV owners https://www.evee.com.au/

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 15 Table 3 Example of annual revenue contribution calculations On-road On-road Annual Litres/ kWh/ Fuel Govt Electric- Total Litres/ kWh/ km year yea r Revenu Fuel ity VAT Govt 100km 100km e $/lt Reven Revenue Revenu (a) (a) (c) ue $/yr $/yr (d) e $/yr Honda Jazz 0 15,000 1,125 0 0 7.5 0.80 900 900 Toyota Prius 0 15,000 0 0 5.1 765 0.80 612 612 Nissan Leaf 0 24.8 15,000 3,720 111 656(b) 0.34 223 334 (a)Table 1 (b) Indirect consumption of diesel fuel assuming 50% of generation from renewable sources. (c) From 2018 Fiscal Duty and VAT values for gasoline and diesel fuel, supplied by FRCS. (d) Based on home charging at $0.331/kWh plus 9% VAT.

EVs could be levied a higher registration fee to recover the value of fuel taxes foregone. This could be calculated from the average annual travel and typical fuel consumption of the current vehicle fleet, as determined by checking the odometer at the annual registration inspections. (In fact, it would in theory be possible to levy a different annual charge for each actual EV based on its travel during the year, but this could only be determined after it is inspected and would set up a further incentive to wind back the odometer).

The electricity used by public or commercial EV chargers can be readily identified and charged accordingly through fully cost-recovering time of use (TOU) and maximum demand tariffs, if so desired. The electricity used by home chargers is more difficult to identify, although the presence of chargers, which could draw up to 10kW, will be known to EFL, since consumers and electricians must report significant changes in connected loads. EV charger owners can therefore be asked to take TOU or maximum demand tariffs, to recover the costs they impose on the network. They might also be required to install chargers with demand response capability, so EFL can interrupt or delay charging at times of network congestion or generation stress.18 Alternatively, it could be a matter of policy not to recover these costs from EVs, as part of the public subsidy that would almost certainly be required to encourage their uptake.

Information required to make an informed judgement

Operating revenue modelling could be combined with estimate of the landed costs of EVs compared with ICVs and the import revenue raised. Table 4 illustrates the differences in revenue at the point of import and over a 10-year operating life from new vehicles of similar sizes but different propulsion types (although new EVs will probably have higher landed costs than other types of similar size). As tariff and duties for EVs have not yet been set, two estimates are given – if EVs were assessed at lower duties (at the same rates as HVs) and at higher duties (at the same rate as ICVs). Table 5 shows a similar calculation for used vehicle imports.

18 The Australian and New Zealand governments are considering a requirement that all residential EV charging points must have demand response capabilities. http://www.energyrating.gov.au/document/consultation-paper-smart-demand-response-capabilities- selected-appliances

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 16 If vehicles of different types have different landed costs this will influence their retail market price. The relationship is complex – retailers can generally charge higher margins for higher price vehicles newly purchased by government and corporate fleets than for used vehicles more likely to be purchased by income-constrained private buyers. The retail purchase price estimates together with the retail fuel and energy price projections and maintenance costs (which should be lower for EVs) will indicate the purchase and operating costs to vehicle owners.

If the annual electricity consumption of EVs is projected, with an estimate of the share supplied by public and home charging, the value of the electricity that would be sold under current commercial and residential tariff structures (and possible alternative structures) could also be calculated.

Table 4 Example of 10-year revenue calculation (new vehicle, CIF value $30,000) Total 10-yr Import + Import Energy 10yr Revenue(a) Revenue(b) Revenue Honda Jazz 1490 cc ICV 9000 9000 18000 Toyota Prius 1490 cc HV 4500 6120 10620 Nissan Leaf EV (low duties) (c) 9000 3340 12340 Nissan Leaf EV (high duties) (d) 4500 3340 7840 (a) based on Fiji tariffs and duties rates applying from 1 July 2019 (b) from Table 3 (c) Tariff and duties as for HV. (d) Tariff and duties as for ICV

Table 5 Example of 10-year revenue calculation (used vehicle, CIF value $12,000) Total 10-yr Import + Import Energy 10yr Revenue(a) Revenue(b) revenue Honda Jazz 1490cc ICV 6240 9000 15240 Toyota Prius 1490cc HV 8600 6120 14720 Nissan Leaf EV (low duties) (c) 6240 3340 9580 Nissan Leaf EV (high duties) (d) 8600 3340 11940 (a) based on Fiji tariffs and duties rates applying from 1 July 2019 (b) from Table 3 (c) Tariff and duties as for HV. (d) Tariff and duties as for ICV

Impact on national balance of payments

If the introduction of EVs leads to a net reduction of fuel imports, by displacing more transport fuels than it adds to the demand for electricity generation fuels, this should assist Fiji’s balance of payments. On the other hand, there would be an increase in the value of vehicle imports if EVs cost more than the current mix of ICVs and HVs.

Information required to make an informed judgement

The operating costs modelling described in the preceding section previous should contain all of the data required to project fuel imports and vehicle imports, in both physical quantity and value terms.

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 17

Potential Negatives

Higher greenhouse gas emissions

If EVs simply transfer fuel combustion from vehicle engines to diesel generators, Fiji’s greenhouse gas emissions could be higher compared with a BAU (no electrification) scenario. This assessment requires consideration of the emissions-intensity of the marginal source of generation on the grid, not the average generation. For example, once existing hydro and other renewable capacity is fully utilised, it cannot be readily expanded to meet future rises in electricity demand in Fiji.

Any daily and yearly shortfall between demand and supply will continue to be made up by diesel. The output of new renewable capacity will be fully utilised as soon as it is built, but diesel will almost certainly remain the marginal fuel when demand exceeds renewable supply.

Information required to make an informed judgement

Careful projection of load growth with and without EVs, and the phasing of renewable and non-renewable generation increments under both scenarios, will be necessary to determine whether emissions will be higher or lower with EVs. Essentially, there will be a “Business as Usual” (BAU) case with few, or minimal EVs, and a range of cases where EVs are introduced at various rates (say 100 new EVs/yr, 1,000 and up to 10,000 – i.e. the rate achieved by HVs in the period 2015-2019).

In each scenario the change in generation output and fuel/renewables mix will be influenced by the rate of EV growth, so the scenarios must be matched. The higher the rate of EV growth the lower the rate of increase in emissions from transport fuels but the higher the emissions from electricity generation. If a scenario shows that electricity sector emissions growing faster than transport fuel emissions falling, it indicates that national emissions from transport electrification will rise.

Vehicle costs

The take-up of vehicles (of any type) is a complex function of household incomes, the absolute and relative price of vehicles and their fuel and other operating costs. Vehicle price is a function of CIF price, taxes and duties and reseller margins. Government policy will influence the relative prices of different vehicle types and fuel types though excise and taxation.

Based on price differentials in other markets, it is likely that EVs will be significantly more expensive than ICVs or HVs, especially as used models will be relatively scarce for some years and there are competing markets for Japanese used EVs (e.g. New Zealand).19 The cost of maintenance and servicing may also be different.

19 The cheapest new EV available in Australia, for example, costs about 25% more than an equivalent size ICV. https://www.qld.gov.au/transport/projects/electricvehicles/about/compare

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 18 Higher vehicle prices may have some public policy benefits if they slow the growth rate of car ownership and traffic congestion and encourage walking and cycling. However, public transport may need to be strengthened to meet the demand for motorised mobility. Conversely, if it is government policy to encourage EVs, then knowing the price differentials will be necessary to calculate the amount of subsidy (as lower duty and taxation rates or direct bounties) required to make them cost-competitive.

Information required to make an informed judgement

The Fiji vehicle market has responded strongly to the availability of HVs. The Fiji automotive industry will be well aware of the price factors and other conditions that brought this about and analysing the reasons will help with understanding likely EV costs and their impact on the market. Market segments such as fleets may be less price- sensitive.

Maintenance also affects vehicle ownership costs. The Fiji automotive industry has considerable expertise in servicing conventional petrol and diesel engines, but EV maintenance requires different skills and equipment. Some of these may already be developing to service the growing fleet of hybrid vehicles, but other skills may only be available in Fiji once the rate of EV introduction reaches certain thresholds. For example, local firms will not be able to afford to send technicians to the EV-exporting countries for training unless they are assured of a certain volume of work. The initial feedback from Fiji car retailers is that the minimum sales volume to support this investment is about 100 EVs per year.

Cost of charging infrastructure

There will need to be investment in charging infrastructure ahead of the growth in EV numbers. The first public charging stations will be lightly used for some time, so may need to be publicly owned or supported until they become commercially viable. Depending on their location and capacity (kVA) in relation to the network, they may also require network augmentation.

Information required to make an informed judgement

The costs of charging infrastructure (including any network augmentation) will be significant, and the return on the investment will depend on the location and power of the chargers, the rate of EV development, and the balance of public vs home charging on the network. This is subject to a separate research project.

Battery costs (including end-of-life disposal)

There will be significant costs in replacing and disposing of lithium propulsion battery packs, whether through a formal collection system or the environmental costs of dumping. The costs could be reduced if a battery collection system is first set up for hybrid vehicles.

Information required to make an informed judgement

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 19 The existing patterns of disposal of HV batteries will provide a useful case study, but new research is necessary. The widespread use (and disposal) of automotive lithium ion battery packs is relatively new in Fiji. The Fiji National Solid Waste Management Strategy 2011-2014, published in 2011, refers to recycling of lead-acid batteries, but not lithium ion.

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 20 3. Categories of Information Required

This section summaries the specific categories of data required to undertake the policy studies and evaluations detailed in the preceding section.

The data categories have been grouped into three inter-related clusters:

• Fuels (transport and generation) • Vehicles (transport equipment); and • Travel and mobility.

The clusters and stages are illustrated in Figure 1, along with the agencies broadly responsible for collecting data at each stage. The main collections and publications of data so far identified are listed in Table 6. The following section discusses the data already collected (although not always available in the right form) and how it can be used to support transport electrification planning and cost-benefit analysis.

Vehicles

Number and types of Vehicles

FRCS has published reports of imports of vehicles in a consistent format since July 2016, but the series may go back further. Some reports have been published as PDF and some as XLS, but it is assumed that the underlying data are all held as XLS. An extract is shown at Table 8.

The series identifies HVs because under Government policy they pay a concessional duty. ICVs are not differentiated by type of fuel used (petrol or diesel). While this information could possibly be reconstructed by (laboriously) matching models, it is more easily recovered from the LTA registration database.

The trends in landed costs of different vehicle categories over time could be used (with suitable multipliers for local wholesale and retail on-costs) as a proxy for retail prices. The retail price trends could then be used to build and test a predictive model of vehicle numbers (combined with projections of GDP, household income and other explanatory factors).

The FRCS data series could also be used to calculate the revenue forgone through concessional duty rates, and so inform the testing of revenue impacts of various duty concession scenarios for EVs.

FRCS data may also help clarify the “distribution/ownership” stage of vehicle life, because the custom clearance documentation could reveal the number of imports by private owners, by fleet owners and by dealers/resellers.

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 21 Figure 2 Main Data Categories and Collection Agencies

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 22 Table 6 Summary of major data collections reviewed to date Agency Collection Format Latest & Update frequency Access Plans/comments FRCS Fuel imports $ Regular NPA; AOR; passed to FBOS 1 FRCS Motor vehicle Excel, Mar 2019; approx quarterly since Jul https://www.frcs.org.fj/our-services/customs/doing-business-in-fiji/motor- 2 landing costs (and PDF $, Q 2016 vehicles/ numbers) FBOS Mineral fuel Excel; $ 2019 YTD; Annual since 2005 https://www.statsfiji.gov.fj/index.php/statistics/economic- Broken down to 5 types re- 3 imports statistics/merchandise-trade-statistics; AOR exports significant FBOS Road vehicle Excel; $ 2019 YTD; Annual since 2005 As above Not further broken down 4 imports FBOS Census PDF 2017; every 10 years Some PA; AOR Plan future questions 5 MOIT Fiji Household PDF 2015 (several reports); NPA, AOR (registered users only) https://www.transportfiji.info/wp- 2017 completed but not 6 Travel Survey login.php?redirect_to=https%3A%2F%2Fwww.transportfiji.info%2F&reauth=1 uploaded; 2020 planned MOIT Cruise calls XLS 2014-15; not updated since As above 7 MOIT Vehicle Licence ? ? As above Restricted even to 8 Data registered users MOIT Vehicle XLS 2015; not updated since As above 102,000 records; obviously 9 registrations from LTA MOIT Bus routes & XLS 2015; not updated since As above 10 timetables MOIT Uneconomic XLS 2015; not updated since As above Includes CO2 estimates 11 Maritime routes MOIT Economic XLS 2015; not updated since As above Includes CO2 estimates 12 Maritime routes MOIT Domestic air XLS 2015; not updated since As above Includes litres fuel and 13 routes CO2 estimates LTA Vehicle PDF 2018; annual since 2000 PA https://lta.com.fj/docs/default-source/lta-publications/lta- Summary by registration 14 registrations factsheets/factsheet-1-total-vehicle-registrations-final.pdf?sfvrsn=6 class, not vehicle type LTA Vehicle PDF July 2017; occasional fact sheet PA https://lta.com.fj/docs/default-source/lta-publications/lta- Summary by registration 15 registrations factsheets/factsheet-5--valid-vehicles-july2017.pdf?sfvrsn=2 and vehicle type LTA License holder PDF July 2017; occasional fact sheet PA https://lta.com.fj/docs/default-source/lta-publications/lta- 16 factsheets/factsheet-6--valid-license-holders-july2017.pdf?sfvrsn=2 LTA Monthly regs, PDF July 2017; occasional fact sheet PA https://lta.com.fj/docs/default-source/lta-publications/lta- Shows surge in 2016 – can 17 2017 cf 2016. factsheets/factsheet-7--vehicle-registration-comparison16v17.pdf?sfvrsn=2 match with FCAS data LTA Age profile of XLS This version created by LTA 4 April AO 18 buses and taxis 2019

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 23 Agency Collection Format Latest & Update frequency Access Plans/comments FBOS Vehicle types on PDF By year 2001 – 2017; latest PA https://www.statsfiji.gov.fj/index.php/statistics/other-statistics/registered- Extract from LTA data 19 register publication June 2018 vehicles FBOS Vehicle types PDF By year 2001 – 2017; latest PA https://www.statsfiji.gov.fj/index.php/statistics/other-statistics/registered- Extract from LTA data 20 added to register publication June 2018 vehicles PA = Public access; NPA = No public access; AO = accessible to other agencies; AOR = accessible to other agencies on request; YTD = Year to date Q = quantity

Table 7 Extract from LTA registration database (2015)

Plate Make Model Year Month Engine Fuel First RegisteredUsage Commenced Expiry Registration End date made made Cap cc registered as Toyota COROLLA AE70 1989 1 1452 Petrol 3/11/1999 New Private 15/12/2014 14/12/2015 Lautoka 14/12/2015 Nissan A12 1991 1 1171 Petrol 17/09/1999 New Commercial 18/02/2015 17/02/2016 Ba 17/02/2016 MitsubishiCS3ASNJER 2002 1 1584 Petrol 21/05/2002 New Government 29/09/2014 28/09/2015 Sigatoka 28/09/2015 Toyota PRIUS 2006 10 1490 Petrol 27/08/2015 SecondhandTaxi 27/08/2015 24/08/2016 Valelevu 24/08/2016 Ford PICK UP 1999 1 2499 Petrol 1/12/1999 New Carrier-RSL 20/03/2015 18/03/2016 Labasa 18/03/2016 Hino Not Available 1987 1 6943 Diesel 22/02/2000 New Commercial 24/06/2015 23/06/2016 Rakiraki 23/06/2016 Toyota HIACE CLOSE VAN1989 1 2446 Diesel 22/07/1999 Rebuilt Mini-Bus 7/05/2015 1/03/2016 Sigatoka 1/03/2016 Hino AK3HRK 1997 1 7553 Diesel 1/07/1999 New Road Service 26/05/2015 25/05/2016 Valelevu 25/05/2016 Toyota X-NP80 1992 1 1453 Diesel 15/05/2000 Rebuilt Driving School 13/08/2015 12/08/2016 Taveuni 12/08/2016 Toyota HIACE 2012 3 2494 Diesel 19/07/2012 New Rental 19/07/2015 9/12/2015 Nadi 9/12/2015 Data source 9, Table 6. MOIT Transport Database. Plate numbers have been deleted for confidentiality Table 8 Extract from FRCS Motor Vehicle Landing Costs (Jul-Sept 2018) Environment Import Luxury ECAL,Fiscal New or No. Commercial Description Chassis No. CIF Value and Climate Fiscal Duty Excise Vehicle Duty, IEX LANDING Used Adaption Levy Duty Levy and LVL COST 1 TOYOTA PRIUS ALPHA 1790CC HYBRID ZVW41-3284469 Used 14,617 - 2,500 - - 2,500 17,117 2 TOYOTA PRIUS ALPHA 1790CC HYBRID ZVW41-3006418 Used 15,116 - 2,500 - - 2,500 17,616 3 TOYOTA PRIUS ALPHA 1790CC HYBRID ZVW41-3371510 Used 12,454 - 2,500 - - 2,500 14,954 4 TOYOTA PRIUS ALPHA 1790CC HYBRID ZVW41-3287628 Used 13,786 - 2,500 - - 2,500 16,286 5 TOYOTA PRIUS ALPHA 1790CC HYBRID ZVW41-3284272 Used 14,032 - 2,500 - - 2,500 16,532 6 TOYOTA PRIUS ALPHA 1790CC HYBRID ZVW41-3283991 Used 13,852 - 2,500 - - 2,500 16,352 7 TOYOTA PRIUS ALPHA 1790CC HYBRID ZVW41-3283519 Used 14,672 - 2,500 - - 2,500 17,172 8 TOYOTA PRIUS ALPHA 1790CC HYBRID ZVW41-3282272 Used 11,591 - 2,500 - - 2,500 14,091 9 TOYOTA PRIUS ALPHA 1790CC HYBRID ZVW41-3282230 Used 16,323 - 2,500 - - 2,500 18,823 10 TOYOTA PRIUS ALPHA 1790CC HYBRID ZVW41-3281212 Used 14,791 - 2,500 - - 2,500 17,291 Data source 2, Table 6

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 24 The Final Fiji National Transport Planning Database (data source 6 in Table 6) reports that 24% of urban households and 12% of rural households in Fiji own a car.20 Matching vehicle ownership to household income is best done with current and future surveys by The Fiji Bureau of Statistics (FBOS). The upcoming Household Income and Expenditure Survey (HIES) could ask questions not just about the number of vehicles (if any) owned or used by the household but the broad technology type of each: whether HV, diesel ICV or petrol ICV. In the longer term, as vehicle types are introduced, the same categories should be used in FBOS surveys as in the LTA database (see below).

The most complete data on the vehicle fleet is of course the LTA’s registration database, which is updated continuously as vehicles are registered, re-registered, or removed. No vehicle register is perfect: there are always some unregistered vehicles, and some vehicles still on register may have been scrapped, retired or stolen. However, the need for annual re-registration means that these do not stay on register indefinitely.

Figure 3 illustrates the total number of vehicles on the register at the end of each year, and Figure 4 the number added to the register each year. One of the limits on the rate at which EVs can enter the fleet is the rate of new registrations – e.g. for cars it is about 9,000 per year. Combining the two data sets will give the notional number of annual retirements and test the internal consistency of the data (see Appendix 4).

Table 7 shows an extract from the 2015 LTA register. It is understood that a number of enhancements are planned for the LTA database which will increase its value to all users, including transport policy makers:

• It will show vehicle type (car, bus, motorcycle, trailer etc); so, this will not need to be inferred from ‘usage’ registration; • It will include “propulsion” type (petrol, diesel, HV, PHV, EV, Hydrogen); and • It will show the emissions tier of the vehicle (Pre-euro, Euro 1-7 etc); • There will be a follow-up procedure to check what happens to vehicles whose registration is not renewed; and • The ability of the database to produce reports will be improved.21

It is assumed that this information will be collected for new registrations after June 2019, but it is not clear how much can be recovered for previously registered vehicles. In the meantime, it is possible to estimate HV numbers from the model designations. In 2015 there were 966 Toyota Prius’ on the register. (There are also other models of HV, but the Prius was and remains the most common). This was just before the surge in HV imports.22

The LTA database indicates the size of the vehicle fleets that might be leaders for electrification, but the distribution of vehicle types within those fleets varies. For example, it is understood that only about 10% of the government fleet is cars - the rest are 4-wheel drives and light good vehicles (LGVs). Most of the taxi, hire and rental fleets are cars. Conversely, a number of private cars operate as informal taxis

20 Fiji National Transport Database Final Report April 2016, p26. Cars for private use only; excludes other registered vehicles such as buses, trucks and taxis). 21 Information from CEO of LTA at workshop on 28 June 2019. 22 Industry sources in Fiji estimate that 11,500 HVs were imported in 2016 alone, and another 4,600 have been imported since. The FRCS data could provide a more accurate number.

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 25

Figure 3 Total vehicle registrations, 2001 - 2018

Source: Author analysis of FBOS data sources 19 and 20, Table 6 and information direct from LTA on registrations for the years 2014-2018. FBOS data are sourced from LTA and agree completely the separately supplied LTA data up to 2016. However, there is a small (0.3%) discrepancy between the two sources for a 2017 and a 5.3% discrepancy for 2018. It is assumed that the data provided directly by LTA are accurate and have been used to produce the graph above.

Figure 4 New registrations each year, 2001 – 2018

Source: Author analysis of FBOS data sources 19 and 20, Table 6.

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 26 Market Conditions

Fiji

The LTA database indicates whether vehicles were first registered as new, second-hand or rebuilt. The 2015 breakdown shown in Table 9 indicates that vehicles imported new accounted for 47% of the register.23 It is likely that this share is rapidly falling – of the 2394 vehicles landed in the first quarter of 2019, nearly two-third were used HVs (Data source 2, Table 6). Fully 90% of all cars imported in that period were used HVs from Japan. To fully understand the circumstances that led to this it is necessary to analyse the source market.

Table 9 Total Vehicle Registrations by New/Used, 2015 New 47813 47.0% Second-hand 45299 44.6% Rebuilt 8404 8.3% Unknown 140 0.1% TOTAL 101656 100.0% Source: Author analysis of Data sources 2, Table 6

Source Markets

At present used HVs are price-advantaged in a number of ways:

• the Japanese second-hand vehicle market is over-supplied with used HVs, and it is costly to scrap these in Japan due to high environmental standards. Under the Automobile Recycling Law of 2005, vehicles must be sent to licensed recycling facilities, and refrigerants and air bags removed before the rest is scrapped;24 • The market value of used vehicles in Japan is low, and about 20% of end of life vehicles are available for export cheaply and in large quantities to right- hand-drive (RHD) markets like Fiji; and • due to Fiji government policy, new and used HVs attract lower rates of excise and import duty than other vehicle types.

The conditions of the EV market in Japan are quite different. In 2017 there were less than 100,000 EVs registered in Japan, compared with 7.5 million HVs. In 2018 only 32,000 pure EVs and 20,000 plug-in hybrid vehicles (PHVs) were sold new in Japan. compared with 570,000 HVs.25 This indicates that used Japanese EVs are not likely to be available in quantity for many years.

Of the other possible Asian source countries, China has by far the largest EV fleet (2.5 million) but the South Korea EV fleet is even lower than Japan. In any case, they are unlikely to become sources of second-hand vehicles for Fiji because they are left-hand-

23 It is not known whether “rebuilt” vehicles were imported already rebuilt or rebuilt in Fiji. 24 https://www.japanfs.org/en/news/archives/news_id027816.html 25 About 18,000 units in 2018. https://wattev2buy.com/global-ev-sales/

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 27 drive (LHD) countries whereas Fiji is a RHD country. The LTA does not permit the registration in Fiji of LHD cars, for road safety reasons.

The Chinese EV industry is currently focussed on supplying local demand, but over time it very likely that it will begin exports to both LHD and RHD markets. These will probably be much cheaper than US, European, and Japanese-made EVs, and this may eventually result in significant imports of new Chinese EVs to Fiji.26

Monitoring of the EV markets in Japan and China with regard to trends in technology and price is therefore advisable. The LTA may be well placed to monitor the Japanese market, through its existing contracts with vehicle inspection agencies there.

Other Pacific Markets

Fiji will not be the only market in the region for used RHD EVs. A majority of the 15,000 EVs registered in New Zealand, a RHD country like Fiji, are second-hand Nissan Leafs from Japan.27 Australia has more restrictions on used car imports, so only new EVs can be imported.28 This greatly increases the price of EVs in Australia which, together with a lack of government incentives and a low density of public charging stations, has meant that the Australia has only about 10,000 EVs out of a vehicle fleet of about 19.5 million.

While the Australian market will not be competing with Fiji for used EVs, the New Zealand market will. This means that at first the most likely types of EVs available in Fiji will be very expensive new vehicles or poor-quality used vehicles. In due course China may enter the RHD EV export market and lead to a drop in new EV prices.

Technology and Efficiency

The fuel use and emission impacts of vehicle electrification depend partly on the relative energy-efficiency of the EVs and the probable alternatives, whether ICVs or HVs. The comparison example in the previous chapter was based on the reported efficiencies of 16.5 kWh per 100 km for a Nissan Leaf and 3.4 litres/100 km for a Toyota Prius.

In-use fuel consumption is almost always higher than the values reported from standard dynameter tests. Prasad & Raturi (2018) report about 5.1 litres/100 km (19.8 km/litre) based on their own survey of a sample of Fiji HV owners – about 50% higher than the reported test value.29 It is likely that the on-road consumption of EVs would also be higher than reported test values. However, while there is a long history of reliable information on the actual efficiency and fuel use of ICVs and HVs, there is little reported yet on the actual efficiency of EVs.30 This should be a focus for research with the first EVs imported to Fiji.

26 https://theconversation.com/the-electric-vehicle-revolution-will-come-from-china-not-the-us-116102 27 https://theconversation.com/new-zealand-poised-to-introduce-clean-car-standards-and-incentives-to- cut-emissions-120896 28 https://www.carsales.com.au/editorial/details/new-grey-import-laws-the-facts-108526/ 29 For HV taxis, Prasad & Raturi report 3.7 litres/100km and an average VKT of 69,400. 30 https://www.hindawi.com/journals/jat/2017/4695975/ provides a useful list of references.

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 28 The energy use of Plug-in hybrid vehicles (PHVs) is even more difficult to establish. EVs, HVs and ICVs each use only a singly form of energy (electricity or fuel) whereas PHVs can be topped up either by the fuel tank or the plug, so it is necessary to monitor the consumption of both energy forms. The manufacturer-reported fuel and electricity consumption values of PHVs need to be treated with special caution, because under some standards the test may start with a fully charged battery that is depleted during the test, but the energy that would be required for recharging it (whether from the plug or by running the engine) is not added to the reported fuel consumption.31

Maritime

The prospects for electrification in maritime transport are limited compared with land transport, but there may be some opportunities with outboard motors in small craft, and with ferries on selected short routes. Electric outboard motors rated up to 42kW (equivalent to 70 HP) and inboard marine motors of up to 50 kW are now available.32

According to analysis of MSAF data by Prasad and Raturi (2019) there are about 1,800 registered small craft (<15m) in Fiji. About a quarter of these are owned by resorts and tourism operators, with fleets of up to 8 craft per resort. Electric outboard motors have advantages from the viewpoint of noise, air and water pollution, which would make them attractive for resort use. Electrifying resort fleets also has comparable “eco- marketing” attractions to including EVs in rental car fleets.

There may also be opportunities for small craft operating out of the main urban centres on Viti Levu to use electric outboards. However, practicality and safety issues would limit electrification of small craft on the outer islands. Carrying spare fuel for longer trips is a routine matter (and verifiable by inspection) but ensuring that batteries are sufficiently charged is more complex. Furthermore, many of the outer island villages have limited electricity supply or none at all, so there is no capacity for recharging unless the vessel also carries enough PV panels.

The information needed to investigate these options includes:

• The number of resorts owning and operating small craft powered by outboards; • The size of each fleet, the type of outboards used (2-stroke or 4-stoke) and the patterns of use (number of trips, routes and time available for charging between trips); • Electricity supply and recharging capability; and • Whether the resort owners/managers have considered or would be prepared to consider.

This type of information is best collected by a targeted survey, with sample groups based on MSAF registration data.

31 http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=15&ved=2ahUKEwj7iqfE0_ziAh UOb30KHYB2Af4QFjAOegQICBAC&url=http%3A%2F%2Fwww.mdpi.com%2F2032- 6653%2F5%2F1%2F196%2Fpdf&usg=AOvVaw0j4beTtjdFnbk535t8FF35 32 http://www.aquawatt.at/GB/elektro_aussenbordmotoren_14_GB.html

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 29 Short-haul ferries may provide an opportunity for electrification. At present the shortest inter-island routes may be impractical, but if new commuter routes are established in and around Suva harbour – to Lami and Nausori, example – then electric ferries may be practical.

Travel

The demand for motorised transport is a subset of the demand for travel (moving people) and the demand for freight (moving goods). The 2015 National Household Travel Survey (HTS 2015) reported that walking is by far the most common mode of travel in rural and maritime areas.

In urban areas, 36% of trips were by walking, 27% by private vehicles, 25% by buses and 12% by taxis (12%). As the number of passenger vehicles has increased faster than population since 2015 (for reasons still to be fully analysed), it is likely that the motorised share of urban transport is rising. Nevertheless, walking is probably still the dominant mode even in urban areas, and needs to be catered for in transport planning.

Vehicle Usage

The length of vehicle trips undertaken for various purposes, especially to/from work, is a key input into assessing the prospects for electrification. The 2015 HTS reports trip lengths for all modes (Table 34) but does not cross-tabulate with mode or purpose. This information should be extracted from the base data, which is apparently available at source 6 in Table 6, but is not currently accessible to researchers. The Fiji National Transport Planning Database Final Report reports the average length per car trip as 9.3 km in urban areas but does not report the average daily VKT.

The best available published data on annual vehicle use is from a March 2017 survey of 320 randomly selected drivers, undertaken by Prasad and Raturi (2018). On the basis of responses, they estimate an average usage of 14,800 km/yr for private cars, 69,400 km/yr for taxis, rental and hire cars, 89,800 km/yr for mini vans and 142,800 km/yr for buses. On this basis the average daily VKT for private vehicles would be 40.5 km (well within the range of even a partially charged EV) and for taxis 190km (possibly requiring some recharge during a working day).

The LTA should be in a position to collect reliable annual usage figures from all 120,000 registered vehicles. It is understood that the vehicle odometer reading is recorded at the time of annual inspection, but that this information is not entered against the vehicle on the registration database. If paper records have been retained, then these could be analysed. Alternatively, the LTA might consider making a change to its data management systems to start recording this information.

At present there is no survey comparable to the HTS covering freight transport. Short- haul urban delivery vehicles are another target segment for electrification, so an urban freight survey on the number, type and operations of such vehicles and their average loading would be required. At the first workshop it was reported that:

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 30 • the Fiji Road Haulage Association is undertaking a survey which should help the assessment of the scope for electrified urban delivery vehicles;

• the Fiji Bus Operators Association is undertaking a survey which should yield information on bus routes and overnight garaging, which should help identify the most likely routes and charging options for electrification of bus services.

A larger survey of commercial taxi and hire car operators could also be undertaken, to verify the findings of Prasad and Raturi (2018). Confidentiality would have to be guaranteed so that informal taxi operators would also feel able to participate.

Fuels

Calculating the emissions from the use of fuels requires information on the physical quantity of each type of fuel used. The FRCS and FBOS publicly report imports of the main fuel types by revenue, but not by physical quantity. Physical quantities can be obtained from FRCS and FBOS on request. Prasad and Raturi (2018) have published an estimate of litres of retained fuel imports (imports less exports) for each fuel type from 2010 to 2017, which they attribute to a personal communication from FBOS. This type of information is routinely published in other countries, and it is unusual that it should be subject to a special request.

Annual quantities vary considerably, but mainly due to large fluctuations in aviation fuel retained imports. However, as all aviation fuel is used in aviation these values can be subtracted to yield a much smoother trend in the other fuels: ADO, LPG, gasoline and residual/heavy fuel oil.

However, annual retained imports do not necessarily equate to annual fuel consumption because:

• There are several points of storage along the supply chain, including dockside bulk storages and the tanks of petrol stations. If the volumes held in storage fluctuate significantly between periods, this would impact on estimates of consumption; and

• Locally products biofuels (ethanol and biodiesel) may be added to the fuel stream.

The three main categories of use for non-aviation fuels use are land transport, maritime transport and electricity generation, along with minor use for other purposes such as LPG for cooking and water heating.

It is possible to estimate the fuel used by each of these sectors by either “bottom-up” or “top-down” methods.

Bottom-up methods involve estimating the annual usage (VKT) of each type of vehicle or vessel and multiplying by an estimate fuel consumption value (litres/km). Electricity generation comprises three main components: large EFL diesel generators, smaller EFL plant and private generators of various sizes. Again, fuel use can be inferred “bottom- up” for the largest generators, by multiplying the GWh generation values in EFL’s annual reports by typical litres/kWh values for large plant.

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 31 However, small errors in assumptions of values such as litres/km, annual VKT and litres/kWh generated will lead to large errors in overall fuel estimates. Therefore, it is necessary to reconcile with top-down data:

• actual fuel consumption values from the largest commercial fuel users who keep centralised purchasing records, such as bus, taxi and hire car fleet operators, shipping companies, EFL and large private generators; and

• storage and distribution data from fuel distributors.

Much of this data will be commercial-in-confidence and the entities concerned will be reluctant to provide it. However, it is understood that FBOS has the statutory right to require such information, as well as the obligation not to disclose it in a way that compromises confidentiality. For example, if there are too few companies operating in a particular sector, publication of amalgamated data could allow companies to infer the data for their competitors.

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 32 4. Organising and Facilitating Information Flows

The electrification of the transport sector is clearly a matter of great interest to the Fiji Government, as indicated by Ministerial statements and some budget tax concessions and incentives.33 It would be a development with very significant environmental, economic and social implications, both positive and negative, as indicated in Chapter 2.

Estimating and projecting the outcomes with sufficient confidence to make judgements of the balance of costs and benefits needs to be grounded in reliable information on transport fuel use, vehicle efficiency and technology and travel and mobility. The existing collections of information on these subjects identified during this project are presented in Chapter 3. This chapter relates the roles of the various agencies and identifies some gaps, bottlenecks and opportunities.

Agency Roles

The general area of responsibility of each agency with respect to the data categories needed for transport electrification planning is illustrated in Figure 2. Another way to map the roles of the various agencies is shown in Figure 5. The policy development at the apex of the pyramid needs to be solidly based on actual data readily available for decision-making.

As it happens, the base of the pyramid is well established already. Several agencies routinely collect relevant data, although they do not necessarily make it all public, or not in a consistent and accessible form. The FRCS collects data on all imports, by value as well as by physical quantity. Some of this is published, in a great deal of detail for some collections, such as vehicle imports, and all of it is available to FBOS.

FRCS categorisation of import data is constrained by two major sets of factors: the international ASCUYDA classification system34 and the rates of duty and excise applied to different products and commodities under Fiji law and government policy – for HVs, for example. It will be necessary to ensure that the classification and data systems are consistent with product categories expected from transport electrification: EVs suitable for road registration,35 spare parts such as propulsion battery packs and traction motors, commercial charging stations and domestic charging stations.

FBOS receives primary data from FRCS and other data collecting agencies (LTA and MSAF) and also undertakes its own data collections, including key surveys such as the Census and the Household Income and Expenditure Surveys. For completeness, it also

33 See for example speech by Minister for Transport July 3 2019 https://www.youtube.com/watch?v=YQv_p5VQY4E Incentives in the 2018-19 budget included a 55 per cent capital deduction for any purchase of an electric vehicle, and a seven-year income tax exemption for any business setting up EV charging stations, provided they invest more than $500,000. There has been no take-up. The only measure in the 2019-2020 budget to support the policy is a VAT exemption for “Hybrid and electric ships”. 34 https://asycuda.org/en/about/ ASYCUDA is a computerised customs management system which covers most foreign trade procedures. The system handles manifests and customs declarations, accounting procedures, transit and suspense procedures. It generates trade data that can be used for statistical economic analysis. The ASYCUDA software is developed in Geneva by UNCTAD. 35 As distinct from electric golf buggies, of which there are over 2,300 in Fiji already, according to LTA.

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 33 needs to collect data from public sector fuel users such as EFL (possibly the largest single fuel consumer in Fiji), but appears to have less coverage of private sector entities such as fuel distributors.

Private sector companies and organisations are also part of the base of the information pyramid. Transport industries, where fuel constitutes a major part of business costs, will generally have good records of their overall fuel use and the specific fuel-efficiency of their vehicle or vessel fleets.

Figure 5 The “Information Pyramid”

The next level of the pyramid is analysis of the raw data for specific purposes – in this case to better understand the scope for and implications of electrification in the transport sector. This work is typically undertaken by the relevant policy agencies themselves. Gaps in basic data collection can be filled by special commissioned surveys such as Household Travel Surveys, or academic researchers. In fact one-off special surveys can lead to the acquisition of skills by the commissioning agency, who can later repeat the exercise on their own. This has been the case with the MOIT, who repeated the HTS in 2017, using its own survey staff backed by training by the FBOS.

However, some of the analysis may require the use of data collected by agencies such as FBOS whose statutory constraints may limit disclosure of raw data to the responsible agency. In that case, it may be necessary to specify the analysis in enough detail so FBOS can undertake the analysis and convey the results in the desired formats. FBOS has indicated it is able to do this, subject to funding from the requesting agency and authorisation by its own Minister. Private researchers and academics can also be commissioned to undertake data analytics.

Transport electrification has implications at the highest levels of government policy- making. The apex of the pyramid represents the point at which the implications for Fiji’s emissions trajectory, balance of payments and government finances must be

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 34 assessed. The relevant agencies, including Treasury and the Climate Change and International Cooperation division are within the Ministry of Economy.

Constraints, bottlenecks and gaps

While much of the information required for informed policy-making regarding the electrification of transport in Fiji is already being collected, or could be collected at relatively low cost, there are still constraints and bottlenecks.

Constraints

Constraints are legal restrictions on information flow, often for good public policy reasons. Some agencies are limited by their legislation in what they can release to the public, or even to other agencies. For example, FBOS is restricted by commercial confidentiality rules. Even though data publication is always anonymous – stripped of names – if there are only a few companies operating in a sector then each company may be able to infer the data for the others by subtracting its own data. This may be the case for petroleum product sales, for example, where there are relatively few large companies operating in Fiji.

Personal privacy is another constraint. Collections of data relating to individuals or households should not be transferred to other agencies (let alone published) in a form that permits data records to be directly or indirectly linked to named individuals. For most surveys, names must sometimes be retained for a while to permit re-survey of a small proportion of the total sample to ensure quality control.36 Once verification is complete, the data set should be anonymised by permanently removing names.

Legal constraints do not necessarily prevent one agency supplying information to another, provided that the receiving agency is aware of the legal constraints, undertakes to observe them and has the internal data management procedures and systems to maintain confidentiality. Rather than decide this on a case by case basis, these matters should be covered in written agreements between the agencies.

It could be argued that some data does not need to be made public, so long as it is made available to the agencies responsible for formulating policy, and (with the appropriate safeguards) to their agents (e.g. consultants and researchers). However, making data public increases the likelihood that academics and other researchers will use it for independent analyses, which would reinforce the diversity and robustness of policy inputs at low cost to the government. It would also create a group of regular users, who could check for internal inconsistencies and act as a form of quality control.

Making data public where possible also makes it easier for agencies to know of and access each other’s holdings. The present project found some instances where people were unaware that the data they were interested in, was published on the website of another agency. Making data public also saves time, since agencies do not need to

36 Some data collections require repeat survey of the same cohort of individuals at intervals over several years, but these are generally restricted to health studies and should not be required for transport and energy data.

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 35 respond to and consider special data requests. The default position should be that all information that is not subject to legal, commercial confidentiality or privacy constraints should be made public at a periodic manner.

Bottlenecks

Bottlenecks are administrative rather than legislated limitations on the flow of the information necessary to support transport electrification. They include:

• Unnecessarily high levels of seniority required to initiate data requests to other agencies, to authorise that requests be granted and classify and clear material for upload to data repositories

• Slight differences in what is acquired/recorded; e.g. FRCS records whether a vehicle is a HV (because of excise treatment) but not type of fuel (diesel, gasoline). Until now, LTA has done the opposite (but this is to be rectified in future data acquisitions);

• Maintaining data in hard-to-access media or formats; e.g. keeping annual odometer readings on paper forms but not entering them into the LTA database.

In general, agencies coming under the same Ministry can exchange information more freely than agencies in different Ministries. For example, the TPU should be able to obtain data on request from DOE, LTA, MSAF, although as a statutory body with commercial interests, EFL is in a different category.

Data exchange between ministries appears to be a bottleneck. If MOIT wishes to have regular access to key data, it should consider developing MOUs with FRCS and FBOS for that purpose. FBOS for example has two levels of agreement with agencies – Memorandum of Understanding (MOU) and Agreements.37 MOIT has an Agreement only. At present all data requests to FRCS must be referred to the FRCS CEO. Again, there is the possibility of MOUs with other agencies, and there are some with agencies that require data from FRCS to meet their own regulatory obligations.

Among matters such as confidentiality, MOUs could cover the frequency of data reporting and useability issues such as availability in Excel rather than PDF, and provision of physical quantities as well as monetary values.

The availability of MOIT’s own information could also be improved. The National Transport Planning Database (NTPD) is a good repository of relevant data, surveys and policy studies. However, it does not appear to have been updated since it was set up in 2015. It is understood that later information is waiting to be uploaded, including the 2017 HTS. However, only a small number of senior officers can give clearance to upload information.

Access to the NTPD is restricted, in that users must apply and be cleared for access by MOIT. There appears to be a higher level of access, in that some data sets listed are not

37 At present FBOS has only three MOUs – with FRCS (https://www.frcs.org.fj/news/2018-2/frcs-and- fbos-sign-mou/), the Fiji National Provident Fund FMPF and Investment Fiji.

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 36 accessible even to approved users.38 Other material is clearly non-sensitive, and there is no reason for it not to be in the public domain.

The NTPD would be more useful if there were three levels of access: public, low-level restricted and high-level restricted. MOIT could then then develop guidelines for data classification, so that only material that meets the highest level of sensitivity needs to be referred to senior officers for approval to upload. Information that has been published elsewhere or compiled from published sources should automatically be classified as public and given unrestricted access on the NTPD.

Gaps

There are gaps in analysis, which can be addressed using existing data, and there are gaps in data availability. One example of a gap in analysis is the recent surge in the hybrid share of vehicles imported to Fiji. This provides an ideal case study to inform the development of electrification policy - how was the HV policy developed, what factors helped its implementation and what have been the consequences, both positive and negative?

It is obvious that the safe disposal of batteries is already a major issue with HVs and would be an even greater issue with EVs. This makes it urgent to understand the numbers and lifecycle of lithium ion vehicle batteries in Fiji, and to develop a plan for their management and safe disposal.

Although there is much data already being collected, gaps include:

• A road freight survey, to complement the Household Travel Survey (some gaps may be filled by data being collected by the Fiji Road Haulage Association);

• Surveys of car fleet operators and drivers, to assess their travel patterns and the scope for accommodating EV use and recharging (by time and location);

• Tourism industry EV research: surveys of small boat operations at resorts and tourist car rentals, to assess usage patterns, tourist attitudes to EVs and electric outboards and the scope for recharging; and

• VKT data – this could be collected through the LTA registration system.

Further details of activities to address these and other gaps are given in Chapter 5.

International Data

There are three relevant categories of data from international sources:

1. General information related to EVs and transport electrification, that would enable an initial assessment of environmental and other impacts for any country;

38 For example, clicking on the Raw Dataset for the 2015 HTS returns the message “Sorry, but you do not have permission to view this content.”

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 37 2. Information directly relevant to the development of transport electrification policy in Fiji (and in other countries); and

3. Comparative information on EV statistics, programs and policies across several countries and regions, particularly for countries in the region that are at a similar stage of development as Fiji.

Information of the first type can be used as a starting point when no other data are available. For example, the estimates of maritime CO2-e emissions used in the Fiji LEDS were based on default CO2-e/vessel-km values obtained from broad international averages. These are temporary gap-fillers, in that the default values can be over-written and replaced once actual data for Fiji is acquired.

An example of the second type is up-to-date data on the costs, technology and energy- efficiency of EVs or PHVs of the type likely to be imported to Fiji, and the cost of charging stations. This type of data can only be obtained by regularly monitoring manufacturer and industry news sites and research publications.

An example of the third type is the UNESCAP Asia Pacific Energy Portal, the objectives of which are to:

• Provide open access to DATA and POLICY information on energy and sustainable development. • Enable identification of trends and rapid analysis of data through data visualization and policy cross-sections. • Support informed decision-making among Asia-Pacific energy policy makers. • Support data and policy tracking, research and analysis for regional and global initiatives. 39

The data on such sites tend to lag by several years, since they rely on obtaining government and corporate reports and publications, which themselves usually lag by a year or two, and then introduce a further sorting and uploading delay. In some cases, they assemble data that are compiled by other NGOs annually (at best) rather than continuously. Therefore, they are a “trailing” rather than a leading data source. They tend to be more useful as a repository of policy documents.

39 https://asiapacificenergy.org/

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 38 5. Data Framework and Strategy (DFS)

The objective of the strategy is to enable MOIT to prepare well-founded advice on the costs and benefits of transport electrification from a national perspective. Based on the preceding analysis, this chapter presents a number of tasks and projects which together make up a comprehensive data acquisition and management strategy, or Data Framework and Strategy (DFS) for short.

It is divided into Tasks and Projects. Tasks are on-going activities, including managing information flows, data collections and access, planning data acquisitions, combining existing data sets, analysing new data sets as they become available and reporting progress and problems.

Projects are distinct studies need to support the higher levels in the information pyramid. Some may only need to be done once, and others repeated occasionally as data improves. Apart from the outputs, which are necessary for policy development, undertaking projects will test data the availability and quality of the available data. If it turns out that projects cannot be completed due to inadequate data, this will be a guide for planning future data acquisitions.

Activities are categorised as:

• Organisational arrangements: setting up the framework, maintaining it and reporting on it; • Policy studies and modelling; higher-level analyses that inform the detailed tasks • Analyses of existing and expected data; extracting the most value from what is/will be available; and • Planning and delivering new data acquisitions, making use of scheduled/regular activities, planning new ones if there are gaps.

The following sections give a general description of each activity, the recommended lead agency and the priority. Additional details, including timing and estimated resources for each activity (including additional agencies to be involved) are given in a separate report to MOIT.

A. Organisational arrangements

A1 Overall DFS management, co-ordination and reporting

Description: Developing the DFS workplan, obtaining resources to carry it out, planning each of the 22 detailed activities, reviewing outputs and reporting regularly to policy- makers on progress, achievements and obstacles.

Recommended lead agency: MOIT should have overall responsibility, with this task included in the duty statement of a specific senior position.40 The task should also be

40 In this section “MOIT” covers the Transport and Energy Divisions of the Ministry including the TPU, but it is not currently possible to be more specific. It is understood that the Ministry is in a state of

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 39 formally included in the three-yearly updates of the MOIT’s Strategic Development Plan as well as the annual Corporate Plan, so ensuring that it is covered in annual corporate planning reviews and workshops. Progress should also be covered in the MOIT Annual Report.

Timing: High priority. Commence immediately.

A2 Develop internal data management protocols

Description: MOIT already holds a number of data collections and is constantly acquiring new data related to transport and energy in Fiji (extending well beyond the scope of electrification studies). It does not appear to have a written data management manual or protocol in a form that can be referred to by its own staff or other agencies, or by external actors providing, requesting or using its data.

The protocol should be a document (or set of documents, whether electronic or hard copy) covering, at the least:

• Cyber-security (protection against data theft or compromise); • Rules for data sharing within MOIT (including with LTA); • Guidelines for classification of data (see Task A4); • Who has authority to classify data; • Rules for responding to external data requests; and • Succession planning (e.g. ensuring that data or access to it are not lost if a staff member leaves or changes jobs).

Recommended lead agency: MOIT should have responsibility with regards to managing the transport and energy data collections of the TPU and the DOE and should be aware of the data management protocols of related agencies such as LTA and EFL. (While EFL is technically an “internal” agency under the same Minister, it became apparent during this project that MOIT cannot obtain data from EFL in the same way as it can obtain data from LTA). Timing: High priority. Commence immediately

A3 Make external data sharing arrangements with other Ministries

Description: Review current inter-agency data sharing arrangements (if any) between MOIT and other agencies and private data providers, particularly with FBOS and FRCS, and establish formal MOUs or other arrangements to streamline future data sharing. Ensure these are consistent with high-level guidelines (if any) applying across the Fiji Government. Private providers would include transport industry associations.

Agreements should also cover technical issues such as field structure and terminology for data acquisitions and collections related to transport electrification (e.g. FRCS to create a separate import category for EV chargers of various kVA capacities).

Recommended lead agency: MOIT reorganisation, and the structure at http://www.moit.gov.fj/images/2018/2018%20Org%20Structure.jpg (accessed September 2019) is no longer accurate.

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 40

Timing: High priority. Commence immediately.

A4 Develop consistent cross-agency data classification & access rules

Description: Inconsistent classification of data with regard to its level of confidentiality inhibits its sharing between agencies, and its publication. This task is to develop classification & access rules, initially within MOIT departments and agencies. Once these are settled and adopted within MOIT (as part of Task A2) the same rules could be proposed to the other agencies with which MOIT has data sharing agreements (Tasks A3).

As a starting point, a three-level classification could be used:

• Public (anyone can access, and ideally should be placed on website)) • Restricted (user registration & log-in required, as with the National Transport Planning Database, although most of the material currently on the NTPD could be reclassified as public); and • Confidential (both log-in and higher clearance required).

Recommended lead agency: MOIT

Timing: Medium - High priority. Immediate application to Tasks A3, A5.

A5 Update and maintain National Transport Planning Database (NTPD)

Description: The NTPD has a large amount of data that is useful for general transport policy and planning, as well as for studies of electrification. However, the content has not been updated since it was established in 2015, and access is unnecessarily restricted. This task consists of

• Reviewing the existing content of the NTPD, to remove obsolete material and reclassifying all remaining material as public, restricted or confidential. • Uploading new content where available, such as the 2017 HTS • Classifying all new content as public, restricted or confidential • Moving the public content to a publicly accessible part of the NTPD and setting up two levels of access (restricted and confidential) for the rest (see Task A4).

Recommended lead agency: MOIT

Timing: High priority. Immediate application to Task A4.

B. Policy studies and modelling

B1 Emission scenarios with/without EVs

Description: To test the hypothesis that electrification of transport will in fact reduce Fiji’s greenhouse gas emissions, this project will develop a number of scenarios, combining various rates of EV introduction with various rates of investment in

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 41 renewable energy generation. Low, medium and high scenarios of each will give 9 combinations (more, if overlaid on different rates of growth in general non-transport electricity demand).

Transport sector emissions will chance gradually in each scenario, but electric-related emissions will most likely change in steps according to assumptions about the nature and timing of generation increments. Transport and electricity emissions will need to be added for each future year (say 2020-2040) to give total emissions impacts and enable the scenarios to be compared. Emissions of other pollutants (NMVOC, SOx, NOx etc.) should be calculated in addition to CO2-e.

The scenarios developed for this project can be used in other projects as well, to establish consistency and comparability.

Recommended lead agency: MOIT

Timing: Highest priority, to begin immediately. A realistic assessment of the emissions impact of transport electrification is necessary to inform policy-making.

B2 Fuel consumption, energy-efficiency, charging, range

Description: Determining the impacts of transport electrification by comparing the performance of EVs with their HV and ICV equivalents in each of the market segments where substitution is feasible. After identifying each of these segments, report on:

• The tested energy- and fuel-efficiency values for typical models of each type (EV, HV and ICV, similar to Table 1); • The on-road energy- and fuel-efficiency values; • EV range; • Charging behaviour of EV owners (share of charging expected at home and at public stations); • Estimate of annual fuel consumption and electricity use of comparable EV, HV and ICVs.

Recommended lead agency: LTA

Timing: Medium-High priority. To commence once Fiji policy-makers decide to develop an electrification strategy.

B3 Travel projection scenarios

Description: Project B1 can be undertaken using the same average VKT for all vehicle types within the EV-substitutable sectors. In reality, EVs are likely to be used in different ways and travel different annual distances than similar HVs and ICVs. This project will try to establish realistic usage and travel patterns for EVs, within the context of overall demand for motorised and non-motorised travel. Fleet-owned EVs may be constrained in their VKT by off-road charging time requirements. Alternatively, operating cost advantages may lead to EVs being used in preference to fuel vehicles,

Recommended lead agency: MOIT

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 42

Timing: Medium-High priority. To commence once Fiji policy-makers decide to develop an electrification strategy.

B4 EV market & supply chain study

Description: Investigate likely source countries, landed prices for new and second-hand imports (at various duty, VAT, ECAL rates). Also investigate the supply chains for EVs and spare parts in Fiji, and possible non-price barriers to adoption (lack of local maintenance skills and capacity, road conditions etc.)

Recommended lead agency: LTA

Timing: Medium priority.

B5 Vehicle ownership costs

Description: To estimate the ownership costs for people purchasing EVs in Fiji, compared with HV and ICV alternatives. Include including capital costs (from Project B4) fuel and maintenance costs (from Project B2) and registration charges. Among other matters this will clarify the extent of financial subsidies that may be required to make EVs cost-competitive.

Recommended lead agency: LTA

Timing: Medium priority.

B6 Battery life-cycle, refurbishment and disposal model

Description: The growing number of HV batteries is already an issue for Fiji, and the larger battery packs of EVs will add to the disposal and environmental burden. On the other hand refurbished “second life” battery packs could become a resource for stand- alone PV systems. This project develops a quantified model of the life-cycle of EV propulsion batteries, using the same rang of EV takeup scenarios as in Project B1.

Recommended lead agency: DOE

Timing: Medium priority.

B7 Vehicle purchase econometric model

Description: The projection of vehicle numbers is fundamental to planning for all forms of transportation and is the baseline for testing different EV take-up scenarios. The project is to construct a model integrating the best available data on GDP, incomes, vehicle prices and annual vehicle ownership operating costs from Projects B4 and B5. Once the model had been validated against historical trends it will be used predictively.

Recommended lead agency: University of South Pacific or Fiji National University

Timing: Medium priority, to proceed after or in parallel with Projects B4 and B5.

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 43

B8 Impact on government revenues and national accounts

Description: To estimate the total impact on government revenues under a range of EV duty, excise, VAT rates and other taxes, charges and revenue streams (e.g. from EFL electricity sales). This will be necessary to inform policy-makers about the national financial as well as the environmental impacts of EV-supporting policies.

Recommended lead agency: Ministry of Economy

Timing: High priority.

B9 Impact of EVs on grid stability

Description: To model the impacts of various levels of EV ownership, charging patterns and charging locations on the ability of the EFL electricity grid to meet specifications for voltage, frequency and reliability of supply.

Recommended lead agency: EFL

Timing: Medium-high priority (see parallel project on the ability of Viti Levu grid to support the electrification of transport).

B10 Impact of EVs on utility revenues and costs

Description: To model the impacts of various levels of EV ownership, charging patterns and charging locations on the capital cost program of EFL and on revenues (under various EV charging tariff scenarios), to assess the magnitude of financial subsidies required (if any) to maintain financial viability.

Recommended lead agency: EFL

Timing: Medium-high priority (see parallel project on the ability of Viti Levu grid to support the electrification of transport).

C. Analyses of existing and expected data

C1 Vehicle ownership, usage and expenditures

Description: Combine and cross-tabulate data from existing collections to determine trends in ownership of private vehicles, expenditures on vehicle operation (fuel and maintenance), vehicle usage (VKT/household), garaging, travel by vehicle as a share of all travel and expenditure on electricity by vehicle-owning households (to enable calculations of likely change in bills from shifts to EVs). The data collections include:

• Census 2017 (FBOS) • Household Income and Expenditure Survey 2017 (FBOS) • Household Travel Survey 2015, 2017 (MOIT)

Recommended lead agency: FBOS

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 44

Timing: Medium Priority – commence after 2017 HTS is tabulated

C2 Public transport usage and expenditures

Description: Identify main public transport routes currently served by buses where electric buses could be introduced. For those routes, calculate patronage and estimate revenues using electronic ticket data (held by Vodafone). Also analyses daily passenger and bus movements and peaks to assess number of electric buses (or alternative EVs – ferries on some routes?) and how charging can be scheduled.

Recommended lead agency: MOIT

Timing: Medium Priority

C3 Recurring vehicle fleet trend analysis

Description: As LTA registration database changes, run annual queries to track the following values (cover last 5 years in first iteration, then repeat annually – previous data structures may not yield all values of interest):

• Number of new/used and average age of new registrations in each EV- substitutable vehicle category • Number, average age and average VKT of re-registrations in each EV- substitutable vehicle category • Number of retirements, average age at retirement and average years on register at retirement in each EV-substitutable vehicle category • Location (by street address, if possible) of registrants of registered vehicles in in each EV-substitutable vehicle category (as an anonymised map)

Recommended lead agency: LTA

Timing: Medium-High Priority: First iteration end of 2019 (covering 2015-2019 data) then annual repeats to build up trends.

C4 National energy flow diagrams (last 5 years, then annual)

Description: To describe Fiji’s annual energy consumption and use as a flow diagram (sometimes called a Sankey diagram).41 This will give a visual illustration of the balance between fuels used in electricity generation and in transport (as well as the balance between fuel imports, exports and local biofuel production). It can also be used to illustrate monetary flows.

Recommended lead agency: DOE

Timing: Medium-High Priority: First iteration end of 2019 (covering 2015-2019 data) then annual repeats to build up trends

41 https://www.iea.org/Sankey/

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 45 D. Planning and delivering new data acquisitions

D1 Freight transport study

Description: Identify urban area freight tonnages, vehicles and routes suitable for electric delivery vehicles. Complement the Household Travel Survey (some gaps may be filled by data being collected by the Fiji Road Haulage Association).

Recommended lead agency: MOIT

Timing: Medium Priority: Start planning in early 2020, conduct survey 2020-21.

D2 Surveys of Government, taxi & car fleet operators and drivers

Description: To collect data on both behaviour (by drivers and fleet owners) that could affect the scope for electrification, and attitudes to introduction of EVs. Needs different survey techniques for fleet owners/managers (in-depth interviews?) and drivers (standardised surveys). To cover practices such as private use and home vs central garaging of fleet-owned vehicles.

Recommended lead agency: MOIT

Timing: Medium priority. Start planning 2020, carry out surveys in 2021.

D3 Survey of tourism & car rental operators

Description: Similar to D2 but focus on attitudes of rental car fleet owners/managers to including EVs in rental fleets, and attitudes of resort owner/operators to including EVs and electrically-powered vessels in resort operations.

Recommended lead agency: MOIT

Timing: Medium priority. Start planning 2021, carry out surveys in 2021

D4 Survey of tourists, visitors

Description: To complement D3, by gathering information about whether visitors would prefer rental EVs if available, and attitudes to electric cars and small vessels at resorts (e.g. would it make them more inclined or less to select that resort). Aim is to gather consumer information that could help influence fleet and resort owners/operators.

Recommended lead agency: MOIT

Timing: Medium priority. Start planning 2020, carry out surveys in 2021

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 46 D5 Monitoring upcoming surveys for data acquisition

Description: Monitoring planned and upcoming surveys and studies in Fiji (by FBOS, other government agencies, industry associations and others) to ensure that information can be collected relevant to transport electrification policy, where appropriate.

Recommended lead agency: MOIT

Timing: Medium priority. Start immediately.

Conclusions

The 24 identified activities (on-going tasks and projects) are summarised in Table 10, along with an indicative 3-year timeline. It is recognised that the work will depend on the staff expertise, staff time and financial resources available, and projects are staggered to spread the load. There are 7 high priority activities, mostly involved with establishing the data framework and strategy, and informing two of the threshold issues that policy-makers will need to address:

• What will be the impact of transport electrification on national emissions?; and

• What will be the impact on government revenues and the national economy?

Furthermore, a framework of consistent data terminology and classification, better internal data management practices in the transport and energy portfolio and formal agreements on data exchange with other ministries could provide a model for other Fiji Ministries and public agencies.

*****

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 47 Table 10 Summary and indicative timeline of tasks and projects Task or Description Priority Lead 2019 2020 2021 2022 Project agency Q4 Q1,2 Q3.4 Q1,2 Q3,4 Q1,2 Q3.4 A1 DFS management, coordination etc H MOIT A2 Internal data management protocols H MOIT A3 Data sharing MOUs with other Ministries H MOIT A4 Consistent classification and access rules H MOIT A5 Update & Maintain NTPD H MOIT B1 Emission scenarios with/without EVs H MOIT B2 Fuel consumption, EV energy-efficiency etc M – H LTA B3 Travel projection scenarios M – H MOIT B4 EV market & supply chain study M LTA B5 Vehicle ownership costs M LTA B6 Battery life-cycle model M DOE B7 Vehicle purchase econometric model M USP/FNU B8 Impact of EVs on government revenues H M Econ B9 Impact of EVs on grid stability M – H EFL B10 Impact of EVs on utility revenues and costs M – H EFL C1 Vehicle ownership, usage and expenditures M FBOS C2 Public transport usage and expenditures M MOIT C3 Recurring vehicle fleet trend analysis M – H LTA C4 National energy flow diagrams M – H DOE D1 Freight transport study M MOIT D2 Government, taxi & car fleets study M MOIT D3 Car rental and tourism – EVs and small boats M MOIT D4 Visitor and tourist attitudes M MOIT D5 Monitor upcoming surveys M MOIT Planning or period between repeat activities Implementation or active period

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 48 References

Documents Bell (2016) Review of Fiji Maritime and Freight Sector, Final Report, Michael Bell for Predict Consulting, April 2016

NTPD (23016) Fiji National Transport Planning Database; Final Report April 2016

HTS (2015) National Household Travel Survey, Fiji 2015; Technical Report, Kate Mackay Consulting for Predict Consulting. Prepared for: The Transport Planning Unit, Ministry of Infrastructure and Transport, April 2016

Prasad & Raturi (2018) Low-carbon measures for Fiji’s land transport energy system, Ravita D. Prasad, Atul Raturi, Utilities Policy 54, 2018

Prasad & Raturi (2019) Fuel demand and emissions for maritime sector in Fiji: Current status and low-carbon strategies. Ravita D. Prasad, Atul Raturi, Marine Policy 102, 2019

Websites https://www.frcs.org.fj/ http://www.economy.gov.fj/sections/financial-and-asset-management/treasury.html https://www.statsfiji.gov.fj/ http://www.moit.gov.fj/ https://www.abc.net.au/news/2019-07-04/fact-check3a-is-it-correct-that-driving-from- sydney-to-melbour/11267090 https://theicct.org/sites/default/files/publications/Lab-to-road-intl_ICCT-white- paper_06112017_vF.pdf https://theconversation.com/new-zealand-poised-to-introduce-clean-car-standards-and- incentives-to-cut-emissions-120896 https://www.youtube.com/watch?v=YQv_p5VQY4E http://global.chinadaily.com.cn/a/201903/04/WS5c7cb83fa3106c65c34ec994.html https://oppositelock.kinja.com/owning-a-car-in-japan-myths-and-reality-1770442115 https://www.carsales.com.au/editorial/details/new-grey-import-laws-the-facts-108526/ https://www.japanfs.org/en/news/archives/news_id027816.html https://www.abc.net.au/radio-australia/programs/pacificbeat/are-electric-cars-feasible- in-the-pacific/11002594 https://www.unescap.org/sites/default/files/Asia%20Pacific%20Energy%20Portal.pdf

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 49 Appendix 1. Stakeholders Consulted

Ministry of Infrastructure and Transport Mr. Taitusi Vakadravuyaca, Permanent Secretary of Infrastructure and Transport

Transport Planning Unit Ms. Faranisese Kinivuwai (Director, Transport) Ms. Lesi Vuatalevu (Acting Director Transport - TPU) Ms. Aseri Driu (Senior Transport Officer -TPU) Mr. Josua Biulailai (Transport Analyst) Ms. Kesaia Masirewa (Transport Analyst) Ms. Kacaraini Mucunabitu (Transport Officer)

Department of Energy Mr. Mikaele Belena (Director of Energy) Mr. Joji Wata (Research Officer) Mr. Jeke Pai (Biofuel Engineer)

Ministry of Economy Mr. Nilesh Prakash (Head of Climate Change and International Cooperation) Ms. Deepitika Chand (Climate Change Officer) Mr. Prashant Chandra (Climate Change Officer)

Land Transport Authority Mr. Samuel Simpson (Chief Executive Officer) Ms. Leba Raravula (Public Relations Officer)

Energy Fiji Limited Mr. Krishneel Prasad (Team Leader – Utility Design and Network Planning)

Maritime Safety Authority of Fiji Captain Tomasi Kete (Manager Qualification and Licensing) Mr. Akariva Kua (Manager Shipping Inspection)

Fiji Bureau of Statistics Mr. Kemueli Naiqama (Deputy Government Statistician)

Fiji Revenue and Customs Service Mr. Fazul Rahman (Director Revenue Management) Mr. Andrew Malani (Deputy Director Revenue) Ms. Mereia Waqa (Senior Customs Officer)

University of the South Pacific Dr. Atul Raturi (Head of Engineering and Environmental)

Fiji National University Ms. Ravita Prasad (Senior Lecturer)

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 50 Micronesian Centre for Sustainable Transport Mr. Andrew Irvin (Transport Researcher/Consultant)

Asco Motors Fiji (Toyota) Mr. Craig Sims (Chief Executive Officer) Mr. Seiji Tokito (General Manager Sales)

Fiji Bus Owners Association Mr. Richard Lal (President) Mr. Rohit Latchan (General Secretary)

Fiji Roads Authority Mr. Michael Dale (Head of Design and Procurement)

Fiji Motor Traders Association Mr. Suresh Singh (President)

Shreedhar Motors Mr Jagdish Chand (National Manager Sales and Marketing)

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 51 Appendix 2. First Stakeholder Workshop, 28 June 2019

STAKEHOLDER WORKSHOP: ENERGY AND TRANSPORT DATA AUDIT FOR ELECTRIFICATION OF TRANSPORT SECTOR Time : 08:30 to 16:00 Date : Friday 28 June 2019 Location : Government Training Centre, Nasese . FINAL AGENDA Time Item Facilitator 08:00 – 08:30 Registration Ms. Rosi Banuve, Senior Admin Associate, GGGI Session 1 – Setting the Scene 08:30 – 08:35 Welcome Master of Ceremony – Ms. Lesi Vuatalevu, Acting Director Transport, MoIT 08:35 – 08:45 Opening Remarks Mr Taitusi Vakadravuyaca, Permanent Secretary, MoIT 08:45 - 09:00 Background to Project, LEDS Ms. Katerina Syngellakis, Pacific Regional Representative, GGGI 09:00 – 09:30 What information do we need for Mr. George Wilkenfeld, Data Audit sound policy making? Consultant, GGGI 09:30 – 10:00 PHOTO SESSION & MORNING TEA Session 2 – Data Holdings - Requirements and Constraints: Transport-Related 10:00 – 10:30 Data Categories, Data Holdings and Mr. George Wilkenfeld, Data Audit Information Required Consultant, GGGI 10:30 – 11:15 Group Break Out Session 3 groups: Electricity, Transport, and Socio- Economic Data 11:15 – 12:00 Feedback from groups: Information Mr. George Wilkenfeld, Data Audit flows and Mapping Consultant, GGGI 12:00 – 13:00 LUNCH Session 3 – Data Gaps, Flows and Bottlenecks: Transport and Electricity 13:00 - 13.30 Gaps, flows and bottlenecks in Mr. George Wilkenfeld, Data Audit transport and travel data Consultant, GGGI 13:30– 14:00 Electricity-related data needs Mr. Oliver Broughton, EV Study Consultant, GGGI 14:00 – 14:45 Group Break Out Session 3 selective groups: each examining data gaps, flows and bottlenecks in the transport and electricity sector. 14:45 – 15:15 AFTERNOON TEA Session 4 – Next Steps 15:15 – 15:30 Feedback from breakout session Group facilitators groups. 15:30 – 15:45 Next steps in the process – towards Mr. George Wilkenfeld, Data Audit a data management strategy Consultant, GGGI 15:45 – 1600 Summary and Close Remarks Ms. Katerina Syngellakis, Pacific Regional Representative, GGGI

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 52 Attendees

No. Name Organization Phone Gender 1 Dharmendra Chand Vision Motors +679 9986475 Male 2 George Wilkenfeld Global Green Growth Institute +612 4782 1155 Male 3 Oliver Broughton Global Green Growth Institute +64 277 394 925 Male 4 Samuel Simpson Land Transport Authority +679 2206600 Male 5 Jone Rabuwe Tiko Kece Taxis +679 3345137 Male

6 Amini Civanikoro Tiko Kece Taxis +679 3345137 Male 7 Asaeli Dakuwaqa Tiko Kece Taxis +679 3345137 Male 8 Peni Waqawai Fiji Bureau of Statistics +679 8448545 Male 9 Ambrose Smith Fiji Bureau of Statistics +679 8346897 Male 10 Mark Borg Pacific Island Development Forum +679 9907633 Male 11 Nisar Shah Fiji Bus Operators Association +679 9929881 Male 12 Jagdish Chand Shreedhar Motors +679 2224100 Male 13 Craig Sims Asco Motors +679 9991618 Male 14 Iosefo Maiava United Nations Economic and Social Commission for +679 9991984 Male Asia and the Pacific 15 Vincent Guinaudeau Global Green Growth Institute ----- Male

16 Ajay Kumar Central Buses Company Limited +679 9929963 Male 17 Katerina Syngellakis Global Green Growth Institute +679 9992079 Female 18 Mereia Waqa Fiji Revenue and Customs Services +679 3243045 Female 19 Ajit Singh Fiji Bus Operators Association +679 9906390 Male 20 Ravita Prasad Fiji National University +679 9940870 Female 21 Joji Wata Department of Energy +679 9443387 Male 22 Shelvin Prasad Department of Energy +679 9950383 Male 23 Lesoni . N Transport Planning Unit +679 9950736 Male 24 Koto .N Transport Planning Unit +679 9905444 Male 25 Michael Dale Fiji Roads Authority +679 8963962 Male 26 Tirisa Waqanibalagi Secretariat of the Pacific Community +679 9120944 Female 27 Andrew Irvin University of the South Pacific +679 9079441 Male 28 J. C. Lee Ministry of Infrastructure and Transport +679 2941068 Male 29 Manuqalo Bainivalu Transport Planning Unit +679 7327801 Male 30 Kesaia Masirewa Transport Planning Unit +679 8745758 Female 31 Puamau Bagiono Ministry of Infrastructure and Transport +679 9904041 Male 32 Paulai Bilo Ministry of Infrastructure and Transport +679 9001887 Male 33 Jone Tikoicolo United Nations Economic and Social Commission for 9991975 Male Asia and the Pacific 34 Frank Vukimoala Secretariat of the Pacific Community +679 6007970 Male 35 Karunesh Rao Energy Fiji Limited +679 9927104 Male 36 Ulaiasi Butukoro Global Green Growth Institute +679 9266545 Male 37 Atul Raturi University of the South Pacific +679 9376887 Male

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 53 Appendix 3. Second Stakeholder Workshop, 6 August 2019

FINAL AGENDA 2nd STAKEHOLDER WORKSHOP: ELECTRIFICATION OF TRANSPORT SECTOR DATA AUDITS AND STRATEGIES & THE POTENTIAL OF ELECTRIC VEHICLES IN FIJI Time : 08:30 to 16:15 Date : Tuesday 6 August 2019 Location : PIFS Conference Room (Ratu Sukuna Road, Suva, Fiji) FINAL AGENDA

Time Item Facilitator 08:00 – 08:30 Registration Ms. Rosi Banuve, Senior Admin Associate, GGGI Session 1 – Baselining Transport Patterns 08:30 – 08:35 Housekeeping/Introductions Master of Ceremony, Ms. Lesi Vuatalevu, MoIT 08:35 – 08:50 Welcome/Project Overview UN ESCAP Representative 08:50 – 09:30 Viti Levu Transport Patterns and EV Mr Oliver Broughton - EV Study Consultant, Uptake GGGI 09:30 – 10:00 PHOTO SESSION & MORNING TEA Session 2 – Electric Transport Pathways 10:00 – 10:30 The Asia Pacific Energy Portal Ms. Kira Lamont, UN ESCAP 10:30 – 11:15 Group Break Out Session- Transport 3 groups: to review transport patterns Patterns and EV Uptake hypothesis

11:15 – 11:40 Feedback from breakout session Group facilitators groups. 11:40 – 12:00 Grid Implications for All-Electric Mr Oliver Broughton - EV Study Consultant, Transport GGGI 12:00 – 13:00 LUNCH Session 3 – Data audits and strategies 13:00 – 13:30 Final data audit report Dr. George Wilkenfeld, Data Audit Consultant, GGGI 13:30 – 14:00 Suggested data acquisition and Dr. George Wilkenfeld, Data Audit management strategy; next steps Consultant, GGGI 14:00– 14:45 Group breakout session 3 groups: to consider proposed strategy 14:45 – 15:15 AFTERNOON TEA Session 4 – Towards an agreed strategy 15:15 – 15:30 Feedback from breakout sessions & Group facilitators open discussion 15:30 – 16:00 Next steps in the process - a final Open discussion, all participants data management strategy Facilitator: George Wilkenfeld 16:00 – 16:15 Summary and Closing Remarks Ms. Katerina Syngellakis, Pacific Regional Representative, GGGI

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 54 Attendees

No Name Organization Phone Gender . 1 Shirnay Ram Carpenters Motors +679 9996351 Male 2 Penaia Votadroka Maritime Safety Authority of Fiji +679 8916817 Male 3 George Wilkenfeld Global Green Growth Institute +612 4782 1155 Male 4 Oliver Broughton Global Green Growth Institute +64 277 394 925 Male 5 Deepitika Chand Climate Change and International Cooperation +679 9359036 Female Division, Ministry of Economy 6 Deepak Chand Department of Energy +679 9982728 Male 7 Shelvin Prasad Department of Energy +679 9950383 Male 8 Sanjesh Naidu United Nations Economic and Social Commission ------Male for Asia and the Pacific 9 Kacaraini Mucunabitu Transport Planning Unit, Ministry of Infrastructure +679 3389509 Female and Transport 10 Ravita Prasad Fiji National University +679 9940870 Female 11 Manuqalo Bainivalu Transport Planning Unit, Ministry of Infrastructure +679 7327801 Male and Transport 12 Jagdish Chand Shreedhar Motors +679 2224100 Male 13 Bimlesh Krishna Fiji Bureau of Statistics +679 3315822 Male 14 Nikhil Lal Pacific Island Development Forum +679 9236043 Male 15 Ajay Kumar Central Transport Company Limited +679 9929963 Male 16 Tirisa Wainibalagi Secretariat of the Pacific Community +679 9120944 Female 17 Ponijasi Saulekaleka Tiko Kece Taxis +679 9331772 Male 18 Aminiasi Cinanikoro Tiko Kece Taxis +679 9064628 Male 19 Michael Dale Fiji Roads Authority +679 8936962 Male 20 Karunesh Rao Energy Fiji Limited +679 9927104 Male 21 Faranisese Kinivuwai Transport Planning Unit, Ministry of Infrastructure +679 9904889 Female and Transport 22 Ritika Kumar Fiji Bus Operators Association +679 9991243 Female 23 Mereia Waqa Fiji Revenue and Customs Services +679 3243045 Female 24 Ankeet Prasad Ministry of Economy +679 8636574 Male 25 Tevita Tuibau Ministry of Economy +679 3221298 Male

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 55 Appendix 4. Vehicle Additions and Retirements

Figure 6 Annual retirements from the motor vehicle register

Derived from Figure 3 and Figure 4. Annual retirements = (Annual increase in total registrations) – new registrations. Negative retirements numbers for some vehicle categories indicate either changes in classification or errors in the underlying data. Figure 7 Trend in total registrations

Derived from data underlying Figure 3

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 56 Figure 8 Trend in annual retirements

Derived from data underlying Figure 4

Energy and Transport Data Audit for Electrification of the Fiji Transport Sector 57